Running examples in ‘HH-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mmc
> ### Title: MMC (Mean-mean Multiple Comparisons) plots.
> ### Aliases: mmc MMC multicomp multicomp.mmc mmc mmc.glht mmc.default
> ###   [.mmc.multicomp
> ### Keywords: hplot htest design
> 
> ### ** Examples
> 
> ## Use mmc with R.
> ## Use multicomp.mmc with S-Plus.
> 
> ## data and ANOVA
> ## catalystm example
> data(catalystm)
> 
> bwplot(concent ~ catalyst, data=catalystm,
+        scales=list(cex=1.5),
+        ylab=list("concentration", cex=1.5),
+        xlab=list("catalyst",cex=1.5))
> 
> 
> catalystm1.aov <- aov(concent ~ catalyst, data=catalystm)
> summary(catalystm1.aov)
            Df Sum Sq Mean Sq F value  Pr(>F)   
catalyst     3  85.68   28.56   9.916 0.00144 **
Residuals   12  34.56    2.88                   
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> 
> catalystm.mca <-
+ glht(catalystm1.aov, linfct = mcp(catalyst = "Tukey"))
> confint(catalystm.mca)

	 Simultaneous Confidence Intervals

Multiple Comparisons of Means: Tukey Contrasts


Fit: aov(formula = concent ~ catalyst, data = catalystm)

Quantile = 2.9683
95% family-wise confidence level
 

Linear Hypotheses:
           Estimate lwr      upr     
B - A == 0 -1.12500 -4.50421  2.25421
C - A == 0 -3.66667 -7.34549  0.01215
D - A == 0 -5.77500 -9.15421 -2.39579
C - B == 0 -2.54167 -6.38907  1.30574
D - B == 0 -4.65000 -8.21200 -1.08800
D - C == 0 -2.10833 -5.95574  1.73907

> plot(catalystm.mca)                      ## multcomp plot
> mmcplot(catalystm.mca, focus="catalyst") ## HH plot
> 
> ## pairwise comparisons
> catalystm.mmc <-
+   mmc(catalystm1.aov, focus="catalyst")
> catalystm.mmc
Tukey contrasts
Fit: aov(formula = concent ~ catalyst, data = catalystm) 
Estimated Quantile = 2.967811 
95% family-wise confidence level
$mca
    estimate   stderr       lower    upper   height
A-B 1.125000 1.138447 -2.25369630 4.503696 56.33750
A-C 3.666667 1.239385 -0.01159196 7.344925 55.06667
B-C 2.541667 1.296179 -1.30514829 6.388482 54.50417
A-D 5.775000 1.138447  2.39630370 9.153696 54.01250
B-D 4.650000 1.200029  1.08854140 8.211459 53.45000
C-D 2.108333 1.296179 -1.73848162 5.955148 52.17917
$none
  estimate    stderr    lower    upper   height
A 56.90000 0.7589649 54.64754 59.15246 56.90000
B 55.77500 0.8485486 53.25667 58.29333 55.77500
C 53.23333 0.9798195 50.32541 56.14125 53.23333
D 51.12500 0.8485486 48.60667 53.64333 51.12500
> 
> ## Not run: 
> ##D ## these three statements are identical for a one-way aov
> ##D   mmc(catalystm1.aov)  ## simplest
> ##D   mmc(catalystm1.aov, focus="catalyst") ## generalizes to higher-order designs
> ##D   mmc(catalystm1.aov, linfct = mcp(catalyst = "Tukey")) ## glht arguments
> ## End(Not run)
> 
> mmcplot(catalystm.mmc, style="both")
Warning in formals(fun) : argument is not a function
> 
> 
> ## User-Specified Contrasts
> ## Row names must include all levels of the factor.
> ## Column names are the names the user assigns to the contrasts.
> ## Each column must sum to zero.
> catalystm.lmat <- cbind("AB-D" =c( 1, 1, 0,-2),
+                         "A-B"  =c( 1,-1, 0, 0),
+                         "ABD-C"=c( 1, 1,-3, 1))
> dimnames(catalystm.lmat)[[1]] <- levels(catalystm$catalyst)
> catalystm.lmat
  AB-D A-B ABD-C
A    1   1     1
B    1  -1     1
C    0   0    -3
D   -2   0     1
> 
> catalystm.mmc <-
+ mmc(catalystm1.aov,
+        linfct = mcp(catalyst = "Tukey"),
+        focus.lmat=catalystm.lmat)
> catalystm.mmc
Tukey contrasts
Fit: aov(formula = concent ~ catalyst, data = catalystm) 
Estimated Quantile = 2.966902 
95% family-wise confidence level
$mca
    estimate   stderr       lower    upper   height
A-B 1.125000 1.138447 -2.25266136 4.502661 56.33750
A-C 3.666667 1.239385 -0.01046527 7.343799 55.06667
B-C 2.541667 1.296179 -1.30396996 6.387303 54.50417
A-D 5.775000 1.138447  2.39733864 9.152661 54.01250
B-D 4.650000 1.200029  1.08963231 8.210368 53.45000
C-D 2.108333 1.296179 -1.73730330 5.953970 52.17917
$none
  estimate    stderr    lower    upper   height
A 56.90000 0.7589649 54.64823 59.15177 56.90000
B 55.77500 0.8485486 53.25744 58.29256 55.77500
C 53.23333 0.9798195 50.32631 56.14036 53.23333
D 51.12500 0.8485486 48.60744 53.64256 51.12500
$lmat
      estimate   stderr     lower    upper   height
A-B   1.125000 1.138447 -2.252661 4.502661 56.33750
ABD-C 1.366667 1.088144 -1.861749 4.595082 53.91667
AB-D  5.212500 1.021788  2.180956 8.244044 53.73125
> 
> mmcplot(catalystm.mmc, style="both", type="lmat")
Warning in formals(fun) : argument is not a function
> 
> 
> ## Dunnett's test
> ## weightloss example
> data(weightloss)
Warning in data(weightloss) : data set ‘weightloss’ not found
> bwplot(loss ~ group, data=weightloss,
+        scales=list(cex=1.5),
+        ylab=list("Weight Loss", cex=1.5),
+        xlab=list("group",cex=1.5))
Error in eval(substitute(groups), data, environment(formula)) : 
  object 'weightloss' not found
Calls: bwplot -> bwplot.formula -> eval
Execution halted