checkRd: (-1) BANOVA-package.Rd:29: Lost braces; missing escapes or markup?
    29 |   where \eqn{Z_{s,k} }is an element of \eqn{Z}, a \eqn{S \times Q} matrix of covariates. \eqn{\theta_{j,k}^p} is a hyperparameter which captures the effects of between-subjects factor \eqn{q} on the parameter \eqn{\beta_{j,s}^p} of within-subjects factor p. The error \eqn{\delta_{j,s}^p} is assumed to be normal: \eqn{\delta_{j,s}^p} {~} \eqn{N(0,\sigma_p^{-2} )}. Proper, but diffuse priors are assumed: \eqn{\theta_{j,k}^p} {~} \eqn{N(0,\gamma)}, and \eqn{\sigma_p^{-2}} {~} \eqn{Gamma(a,b)}, where \eqn{\gamma,a,b} are hyper-parameters. The default setting is \eqn{\gamma = 10^{-4}, a = 1, b = 1}. \cr
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checkRd: (-1) BANOVA-package.Rd:29: Lost braces; missing escapes or markup?
    29 |   where \eqn{Z_{s,k} }is an element of \eqn{Z}, a \eqn{S \times Q} matrix of covariates. \eqn{\theta_{j,k}^p} is a hyperparameter which captures the effects of between-subjects factor \eqn{q} on the parameter \eqn{\beta_{j,s}^p} of within-subjects factor p. The error \eqn{\delta_{j,s}^p} is assumed to be normal: \eqn{\delta_{j,s}^p} {~} \eqn{N(0,\sigma_p^{-2} )}. Proper, but diffuse priors are assumed: \eqn{\theta_{j,k}^p} {~} \eqn{N(0,\gamma)}, and \eqn{\sigma_p^{-2}} {~} \eqn{Gamma(a,b)}, where \eqn{\gamma,a,b} are hyper-parameters. The default setting is \eqn{\gamma = 10^{-4}, a = 1, b = 1}. \cr
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checkRd: (-1) BANOVA-package.Rd:29: Lost braces; missing escapes or markup?
    29 |   where \eqn{Z_{s,k} }is an element of \eqn{Z}, a \eqn{S \times Q} matrix of covariates. \eqn{\theta_{j,k}^p} is a hyperparameter which captures the effects of between-subjects factor \eqn{q} on the parameter \eqn{\beta_{j,s}^p} of within-subjects factor p. The error \eqn{\delta_{j,s}^p} is assumed to be normal: \eqn{\delta_{j,s}^p} {~} \eqn{N(0,\sigma_p^{-2} )}. Proper, but diffuse priors are assumed: \eqn{\theta_{j,k}^p} {~} \eqn{N(0,\gamma)}, and \eqn{\sigma_p^{-2}} {~} \eqn{Gamma(a,b)}, where \eqn{\gamma,a,b} are hyper-parameters. The default setting is \eqn{\gamma = 10^{-4}, a = 1, b = 1}. \cr
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checkRd: (-1) BANOVA.Bernoulli.Rd:56: Lost braces; missing escapes or markup?
    56 |   \eqn{y_i} {~} \eqn{Binomial(1,p_i)}, \eqn{p_i = logit^{-1}(\eta_i)} \cr
       |             ^
checkRd: (-1) BANOVA.Binomial.Rd:59: Lost braces; missing escapes or markup?
    59 |   \eqn{y_i} {~} \eqn{Binomial(ntrials,p_i)}, \eqn{p_i = logit^{-1}(\eta_i)} \cr
       |             ^
checkRd: (-1) BANOVA.Normal.Rd:58: Lost braces; missing escapes or markup?
    58 |   \eqn{y_i} {~} \eqn{Normal(\eta_i,\sigma^{-2})} \cr
       |             ^
checkRd: (-1) BANOVA.Normal.Rd:59: Lost braces; missing escapes or markup?
    59 |   where \eqn{\eta_i = \sum_{p = 0}^{P}\sum_{j=1}^{J_p}X_{i,j}^p\beta_{j,s_i}^p}, \eqn{s_i} is the subject id of response \eqn{i}, \eqn{\sigma^{-2}} {~} {Gamma(\eqn{\alpha,\beta})}. see \code{\link{BANOVA-package}}
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checkRd: (-1) BANOVA.Normal.Rd:59: Lost braces
    59 |   where \eqn{\eta_i = \sum_{p = 0}^{P}\sum_{j=1}^{J_p}X_{i,j}^p\beta_{j,s_i}^p}, \eqn{s_i} is the subject id of response \eqn{i}, \eqn{\sigma^{-2}} {~} {Gamma(\eqn{\alpha,\beta})}. see \code{\link{BANOVA-package}}
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checkRd: (-1) BANOVA.Poisson.Rd:54: Lost braces; missing escapes or markup?
    54 |   \eqn{y_i} {~} \eqn{Poisson(\lambda_i)}, \eqn{\lambda_i = exp(\eta_i + \epsilon_i)} \cr
       |             ^
checkRd: (-1) BANOVA.T.Rd:57: Lost braces; missing escapes or markup?
    57 |   \eqn{y_i} {~} \eqn{t(\nu, \eta_i,\sigma^{-2})} \cr
       |             ^
checkRd: (-1) BANOVA.T.Rd:58: Lost braces; missing escapes or markup?
    58 |   where \eqn{\eta_i = \sum_{p = 0}^{P}\sum_{j=1}^{J_p}X_{i,j}^p\beta_{j,s_i}^p}, \eqn{s_i} is the subject id of response \eqn{i}, see \code{\link{BANOVA-package}}. The hyper parameters: \eqn{\nu} is the degree of freedom, \eqn{\nu} {~} {Piosson(\eqn{\lambda})} and \eqn{\sigma} is the scale parameter, \eqn{\sigma^{-2}} {~} {Gamma(\eqn{\alpha, \beta})}.
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checkRd: (-1) BANOVA.T.Rd:58: Lost braces
    58 |   where \eqn{\eta_i = \sum_{p = 0}^{P}\sum_{j=1}^{J_p}X_{i,j}^p\beta_{j,s_i}^p}, \eqn{s_i} is the subject id of response \eqn{i}, see \code{\link{BANOVA-package}}. The hyper parameters: \eqn{\nu} is the degree of freedom, \eqn{\nu} {~} {Piosson(\eqn{\lambda})} and \eqn{\sigma} is the scale parameter, \eqn{\sigma^{-2}} {~} {Gamma(\eqn{\alpha, \beta})}.
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checkRd: (-1) BANOVA.T.Rd:58: Lost braces; missing escapes or markup?
    58 |   where \eqn{\eta_i = \sum_{p = 0}^{P}\sum_{j=1}^{J_p}X_{i,j}^p\beta_{j,s_i}^p}, \eqn{s_i} is the subject id of response \eqn{i}, see \code{\link{BANOVA-package}}. The hyper parameters: \eqn{\nu} is the degree of freedom, \eqn{\nu} {~} {Piosson(\eqn{\lambda})} and \eqn{\sigma} is the scale parameter, \eqn{\sigma^{-2}} {~} {Gamma(\eqn{\alpha, \beta})}.
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checkRd: (-1) BANOVA.T.Rd:58: Lost braces
    58 |   where \eqn{\eta_i = \sum_{p = 0}^{P}\sum_{j=1}^{J_p}X_{i,j}^p\beta_{j,s_i}^p}, \eqn{s_i} is the subject id of response \eqn{i}, see \code{\link{BANOVA-package}}. The hyper parameters: \eqn{\nu} is the degree of freedom, \eqn{\nu} {~} {Piosson(\eqn{\lambda})} and \eqn{\sigma} is the scale parameter, \eqn{\sigma^{-2}} {~} {Gamma(\eqn{\alpha, \beta})}.
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checkRd: (-1) BANOVA.ordMultinomial.Rd:63: Lost braces; missing escapes or markup?
    63 |   {...} \cr
       |   ^
checkRd: (-1) BANOVA.ordMultinomial.Rd:66: Lost braces; missing escapes or markup?
    66 |   where \eqn{\epsilon_i} {~} logistic \eqn{(0,1)}, \eqn{c_\ell, (\ell = 2,...L-1)} are cut points, \eqn{c_\ell} {~} \eqn{N(0, \bar{\sigma}_\ell^2)}, and \eqn{\bar{\sigma}_\ell^2} {~} \eqn{Uniform(0, d)}, with \eqn{d} a hyper-parameter. \cr \eqn{\eta_i = \sum_{p = 0}^{P}\sum_{j=1}^{J_p}X_{i,j}^p\beta_{j,s_i}^p}, \eqn{s_i} is the subject id of response \eqn{i}. see \code{\link{BANOVA-package}}
       |                          ^
checkRd: (-1) BANOVA.ordMultinomial.Rd:66: Lost braces; missing escapes or markup?
    66 |   where \eqn{\epsilon_i} {~} logistic \eqn{(0,1)}, \eqn{c_\ell, (\ell = 2,...L-1)} are cut points, \eqn{c_\ell} {~} \eqn{N(0, \bar{\sigma}_\ell^2)}, and \eqn{\bar{\sigma}_\ell^2} {~} \eqn{Uniform(0, d)}, with \eqn{d} a hyper-parameter. \cr \eqn{\eta_i = \sum_{p = 0}^{P}\sum_{j=1}^{J_p}X_{i,j}^p\beta_{j,s_i}^p}, \eqn{s_i} is the subject id of response \eqn{i}. see \code{\link{BANOVA-package}}
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checkRd: (-1) BANOVA.ordMultinomial.Rd:66: Lost braces; missing escapes or markup?
    66 |   where \eqn{\epsilon_i} {~} logistic \eqn{(0,1)}, \eqn{c_\ell, (\ell = 2,...L-1)} are cut points, \eqn{c_\ell} {~} \eqn{N(0, \bar{\sigma}_\ell^2)}, and \eqn{\bar{\sigma}_\ell^2} {~} \eqn{Uniform(0, d)}, with \eqn{d} a hyper-parameter. \cr \eqn{\eta_i = \sum_{p = 0}^{P}\sum_{j=1}^{J_p}X_{i,j}^p\beta_{j,s_i}^p}, \eqn{s_i} is the subject id of response \eqn{i}. see \code{\link{BANOVA-package}}
       |                                                                                                                                                                                    ^