Running 'betamfx-test.R' [171s]
  Running 'betaor-test.R' [152s]
  Running 'logitmfx-test.R' [1s]
  Comparing 'logitmfx-test.Rout' to 'logitmfx-test.Rout.save' ... OK
  Running 'logitor-test.R' [161s]
  Running 'negbinirr-test.R' [1s]
  Comparing 'negbinirr-test.Rout' to 'negbinirr-test.Rout.save' ... OK
  Running 'negbinmfx-test.R' [1s]
  Comparing 'negbinmfx-test.Rout' to 'negbinmfx-test.Rout.save' ... OK
  Running 'poissonirr-test.R' [1s]
  Comparing 'poissonirr-test.Rout' to 'poissonirr-test.Rout.save' ... OK
  Running 'poissonmfx-test.R' [1s]
  Comparing 'poissonmfx-test.Rout' to 'poissonmfx-test.Rout.save' ... OK
  Running 'probitmfx-test.R' [1s]
  Comparing 'probitmfx-test.Rout' to 'probitmfx-test.Rout.save' ... OK
Running the tests in 'tests/betamfx-test.R' failed.
Complete output:
  > library('mfx')
  Loading required package: sandwich
  Loading required package: lmtest
  Loading required package: zoo
  
  Attaching package: 'zoo'
  
  The following objects are masked from 'package:base':
  
      as.Date, as.Date.numeric
  
  Loading required package: MASS
  Loading required package: betareg
  > 
  > ### Name: betamfx
  > ### Title: Marginal effects for a beta regression.
  > ### Aliases: betamfx print.betamfx
  > 
  > ### ** Examples
  > 
  > # simulate some data
  > set.seed(12345)
  > n = 1000
  > x = rnorm(n)
  > 
  > # beta outcome
  > y = rbeta(n, shape1 = plogis(1 + 0.5 * x), shape2 = (abs(0.2*x)))
  > # use Smithson and Verkuilen correction
  > y = (y*(n-1)+0.5)/n
  > 
  > data = data.frame(y,x)
  > betamfx(y~x|x, data=data)
  Call:
  betamfx(formula = y ~ x | x, data = data)
  
  Marginal Effects:
        dF/dx Std. Err.      z    P>|z|   
  x 0.0225862 0.0080137 2.8184 0.004826 **
  ---
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  > 
  > proc.time()
     user  system elapsed 
     0.95    0.14    1.06 
Running the tests in 'tests/betaor-test.R' failed.
Complete output:
  > library('mfx')
  Loading required package: sandwich
  Loading required package: lmtest
  Loading required package: zoo
  
  Attaching package: 'zoo'
  
  The following objects are masked from 'package:base':
  
      as.Date, as.Date.numeric
  
  Loading required package: MASS
  Loading required package: betareg
  > 
  > ### Name: betaor
  > ### Title: Odds ratios for a beta regression.
  > ### Aliases: betaor print.betaor
  > 
  > ### ** Examples
  > 
  > # simulate some data
  > set.seed(12345)
  > n = 1000
  > x = rnorm(n)
  > 
  > # beta outcome
  > y = rbeta(n, shape1 = plogis(1 + 0.5 * x), shape2 = (abs(0.2*x)))
  > # use Smithson and Verkuilen correction
  > y = (y*(n-1)+0.5)/n
  > 
  > data = data.frame(y,x)
  > betaor(y~x|x, data=data)
  Call:
  betaor(formula = y ~ x | x, data = data)
  
  Odds Ratio:
    OddsRatio Std. Err.      z    P>|z|   
  x  1.149663  0.056905 2.8177 0.004837 **
  ---
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  > 
  > proc.time()
     user  system elapsed 
     0.84    0.17    1.00 
Running the tests in 'tests/logitor-test.R' failed.
Complete output:
  > library('mfx')
  Loading required package: sandwich
  Loading required package: lmtest
  Loading required package: zoo
  
  Attaching package: 'zoo'
  
  The following objects are masked from 'package:base':
  
      as.Date, as.Date.numeric
  
  Loading required package: MASS
  Loading required package: betareg
  > 
  > ### Name: logitor
  > ### Title: Odds ratios for a logit regression.
  > ### Aliases: logitor print.logitor
  > 
  > ### ** Examples
  > 
  > # simulate some data
  > set.seed(12345)
  > n = 1000
  > x = rnorm(n)
  > 
  > # binary outcome
  > y = ifelse(pnorm(1 + 0.5*x + rnorm(n))>0.5, 1, 0)
  > 
  > data = data.frame(y,x)
  > logitor(formula=y~x, data=data)
  Call:
  logitor(formula = y ~ x, data = data)
  
  Odds Ratio:
    OddsRatio Std. Err.      z     P>|z|    
  x   2.46016   0.23729 9.3333 < 2.2e-16 ***
  ---
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  > 
  > proc.time()
     user  system elapsed 
     0.84    0.17    1.01