checkRd: (-1) testcoef.env.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.env.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.env.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                               ^
checkRd: (-1) testcoef.env.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.env.apweights.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with nonconstant errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.env.apweights.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with nonconstant errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.env.apweights.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with nonconstant errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                       ^
checkRd: (-1) testcoef.env.apweights.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with nonconstant errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.env.tcond.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with t-distributed errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                          ^
checkRd: (-1) testcoef.env.tcond.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with t-distributed errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.env.tcond.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with t-distributed errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                         ^
checkRd: (-1) testcoef.env.tcond.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with t-distributed errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                          ^
checkRd: (-1) testcoef.genv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta[[i]] R = A, versus Ha: L beta[[i]] R != A.  The beta is estimated by the groupwise envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta[[i]] = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                         ^
checkRd: (-1) testcoef.genv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta[[i]] R = A, versus Ha: L beta[[i]] R != A.  The beta is estimated by the groupwise envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta[[i]] = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                 ^
checkRd: (-1) testcoef.genv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta[[i]] R = A, versus Ha: L beta[[i]] R != A.  The beta is estimated by the groupwise envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta[[i]] = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.genv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta[[i]] R = A, versus Ha: L beta[[i]] R != A.  The beta is estimated by the groupwise envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta[[i]] = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                         ^
checkRd: (-1) testcoef.henv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the heteroscedastic envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.henv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the heteroscedastic envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.henv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the heteroscedastic envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                               ^
checkRd: (-1) testcoef.henv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the heteroscedastic envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.logit.env.Rd:18: Lost braces
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                     ^
checkRd: (-1) testcoef.logit.env.Rd:18: Lost braces; missing escapes or markup?
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.logit.env.Rd:18: Lost braces; missing escapes or markup?
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.logit.env.Rd:18: Lost braces
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                                                                                                   ^
checkRd: (-1) testcoef.penv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta1 R = A, versus Ha: L beta1 R != A.  The beta is estimated by the partial envelope model.  If L = Ir, R = Ip1 and A = 0, then the test is equivalent to the standard F test on if beta1 = 0.  The test statistics used is vec(L beta1 R - A) hat{Sigma}^{-1} vec(L beta1 R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta1 R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                              ^
checkRd: (-1) testcoef.penv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta1 R = A, versus Ha: L beta1 R != A.  The beta is estimated by the partial envelope model.  If L = Ir, R = Ip1 and A = 0, then the test is equivalent to the standard F test on if beta1 = 0.  The test statistics used is vec(L beta1 R - A) hat{Sigma}^{-1} vec(L beta1 R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta1 R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                      ^
checkRd: (-1) testcoef.penv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta1 R = A, versus Ha: L beta1 R != A.  The beta is estimated by the partial envelope model.  If L = Ir, R = Ip1 and A = 0, then the test is equivalent to the standard F test on if beta1 = 0.  The test statistics used is vec(L beta1 R - A) hat{Sigma}^{-1} vec(L beta1 R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta1 R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                              ^
checkRd: (-1) testcoef.penv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta1 R = A, versus Ha: L beta1 R != A.  The beta is estimated by the partial envelope model.  If L = Ir, R = Ip1 and A = 0, then the test is equivalent to the standard F test on if beta1 = 0.  The test statistics used is vec(L beta1 R - A) hat{Sigma}^{-1} vec(L beta1 R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta1 R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                               ^
checkRd: (-1) testcoef.pois.env.Rd:18: Lost braces
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                     ^
checkRd: (-1) testcoef.pois.env.Rd:18: Lost braces; missing escapes or markup?
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.pois.env.Rd:18: Lost braces; missing escapes or markup?
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.pois.env.Rd:18: Lost braces
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                                                                                                   ^
checkRd: (-1) testcoef.rrenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.rrenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                     ^
checkRd: (-1) testcoef.rrenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                            ^
checkRd: (-1) testcoef.rrenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.rrenv.apweights.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model that accommodates nonconstant error variance.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                          ^
checkRd: (-1) testcoef.rrenv.apweights.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model that accommodates nonconstant error variance.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.rrenv.apweights.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model that accommodates nonconstant error variance.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                         ^
checkRd: (-1) testcoef.rrenv.apweights.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model that accommodates nonconstant error variance.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                                                          ^
checkRd: (-1) testcoef.senv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                       ^
checkRd: (-1) testcoef.senv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                               ^
checkRd: (-1) testcoef.senv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
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checkRd: (-1) testcoef.senv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                       ^
checkRd: (-1) testcoef.stenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the simultaneous envelope model.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.stenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the simultaneous envelope model.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
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checkRd: (-1) testcoef.stenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the simultaneous envelope model.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                            ^
checkRd: (-1) testcoef.stenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the simultaneous envelope model.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.sxenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model in the predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                              ^
checkRd: (-1) testcoef.sxenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model in the predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                      ^
checkRd: (-1) testcoef.sxenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model in the predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.sxenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model in the predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                              ^
checkRd: (-1) testcoef.xenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                   ^
checkRd: (-1) testcoef.xenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                           ^
checkRd: (-1) testcoef.xenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.xenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                   ^
checkRd: (-1) xenv.Rd:28: Lost braces; missing escapes or markup?
    28 | \item{eta}{The estimated eta.  According to the envelope parameterization, beta = Gamma * Omega^{-1} * eta.}
       |                                                                                                 ^