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CHECK report for EBarrays on tokay2

This page was generated on 2018-10-17 08:32:06 -0400 (Wed, 17 Oct 2018).

Package 424/1561HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
EBarrays 2.44.0
Ming Yuan
Snapshot Date: 2018-10-15 16:45:08 -0400 (Mon, 15 Oct 2018)
URL: https://git.bioconductor.org/packages/EBarrays
Branch: RELEASE_3_7
Last Commit: 4460f5d
Last Changed Date: 2018-04-30 10:34:59 -0400 (Mon, 30 Apr 2018)
malbec2 Linux (Ubuntu 16.04.1 LTS) / x86_64  OK  OK  OK UNNEEDED, same version exists in internal repository
tokay2 Windows Server 2012 R2 Standard / x64  OK  OK [ OK ] OK UNNEEDED, same version exists in internal repository
merida2 OS X 10.11.6 El Capitan / x86_64  OK  OK  OK  OK UNNEEDED, same version exists in internal repository

Summary

Package: EBarrays
Version: 2.44.0
Command: C:\Users\biocbuild\bbs-3.7-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:EBarrays.install-out.txt --library=C:\Users\biocbuild\bbs-3.7-bioc\R\library --no-vignettes --timings EBarrays_2.44.0.tar.gz
StartedAt: 2018-10-17 01:43:55 -0400 (Wed, 17 Oct 2018)
EndedAt: 2018-10-17 01:45:22 -0400 (Wed, 17 Oct 2018)
EllapsedTime: 87.4 seconds
RetCode: 0
Status:  OK  
CheckDir: EBarrays.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   C:\Users\biocbuild\bbs-3.7-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:EBarrays.install-out.txt --library=C:\Users\biocbuild\bbs-3.7-bioc\R\library --no-vignettes --timings EBarrays_2.44.0.tar.gz
###
##############################################################################
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* using log directory 'C:/Users/biocbuild/bbs-3.7-bioc/meat/EBarrays.Rcheck'
* using R version 3.5.1 Patched (2018-07-24 r75005)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* using option '--no-vignettes'
* checking for file 'EBarrays/DESCRIPTION' ... OK
* this is package 'EBarrays' version '2.44.0'
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'EBarrays' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
Packages listed in more than one of Depends, Imports, Suggests, Enhances:
  'Biobase' 'lattice' 'methods'
A package should be listed in only one of these fields.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* loading checks for arch 'i386'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
* loading checks for arch 'x64'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... NOTE
'library' or 'require' call to 'lattice' which was already attached by Depends.
  Please remove these calls from your code.
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
prepare_Rd: crit.fun.Rd:51: Dropping empty section \keyword
prepare_Rd: ebplots.Rd:116-117: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files for i386 is not available
Note: information on .o files for x64 is not available
File 'C:/Users/biocbuild/bbs-3.7-bioc/R/library/EBarrays/libs/i386/EBarrays.dll':
  Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran)

Compiled code should not call entry points which might terminate R nor
write to stdout/stderr instead of to the console, nor use Fortran I/O
nor system RNGs. The detected symbols are linked into the code but
might come from libraries and not actually be called.

See 'Writing portable packages' in the 'Writing R Extensions' manual.
* checking files in 'vignettes' ... OK
* checking examples ...
** running examples for arch 'i386' ... OK
** running examples for arch 'x64' ... OK
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
** running tests for arch 'i386' ...
  Running 'test.R'
 OK
** running tests for arch 'x64' ...
  Running 'test.R'
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in 'inst/doc' ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 4 NOTEs
See
  'C:/Users/biocbuild/bbs-3.7-bioc/meat/EBarrays.Rcheck/00check.log'
for details.

Installation output

EBarrays.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   C:\cygwin\bin\curl.exe -O https://malbec2.bioconductor.org/BBS/3.7/bioc/src/contrib/EBarrays_2.44.0.tar.gz && rm -rf EBarrays.buildbin-libdir && mkdir EBarrays.buildbin-libdir && C:\Users\biocbuild\bbs-3.7-bioc\R\bin\R.exe CMD INSTALL --merge-multiarch --build --library=EBarrays.buildbin-libdir EBarrays_2.44.0.tar.gz && C:\Users\biocbuild\bbs-3.7-bioc\R\bin\R.exe CMD INSTALL EBarrays_2.44.0.zip && rm EBarrays_2.44.0.tar.gz EBarrays_2.44.0.zip
###
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##############################################################################


  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed

  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
100  242k  100  242k    0     0  4042k      0 --:--:-- --:--:-- --:--:-- 4490k

install for i386

* installing *source* package 'EBarrays' ...
** libs
C:/Rtools/mingw_32/bin/gcc  -I"C:/Users/BIOCBU˜1/BBS-3˜1.7-B/R/include" -DNDEBUG     -I"C:/extsoft/include"     -O3 -Wall  -std=gnu99 -mtune=generic -c ebarrays.c -o ebarrays.o
C:/Rtools/mingw_32/bin/gcc -shared -s -static-libgcc -o EBarrays.dll tmp.def ebarrays.o -LC:/extsoft/lib/i386 -LC:/extsoft/lib -LC:/Users/BIOCBU˜1/BBS-3˜1.7-B/R/bin/i386 -lR
installing to C:/Users/biocbuild/bbs-3.7-bioc/meat/EBarrays.buildbin-libdir/EBarrays/libs/i386
** R
** data
** demo
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
  converting help for package 'EBarrays'
    finding HTML links ... done
    EBarrays-Internal                       html  
    crit.fun                                html  
    ebarraysFamily-class                    html  
    ebplots                                 html  
    emfit                                   html  
    gould                                   html  
    postprob                                html  
    utilities                               html  
** building package indices
** installing vignettes
** testing if installed package can be loaded
In R CMD INSTALL

install for x64

* installing *source* package 'EBarrays' ...
** libs
C:/Rtools/mingw_64/bin/gcc  -I"C:/Users/BIOCBU˜1/BBS-3˜1.7-B/R/include" -DNDEBUG     -I"C:/extsoft/include"     -O2 -Wall  -std=gnu99 -mtune=generic -c ebarrays.c -o ebarrays.o
C:/Rtools/mingw_64/bin/gcc -shared -s -static-libgcc -o EBarrays.dll tmp.def ebarrays.o -LC:/extsoft/lib/x64 -LC:/extsoft/lib -LC:/Users/BIOCBU˜1/BBS-3˜1.7-B/R/bin/x64 -lR
installing to C:/Users/biocbuild/bbs-3.7-bioc/meat/EBarrays.buildbin-libdir/EBarrays/libs/x64
** testing if installed package can be loaded
* MD5 sums
packaged installation of 'EBarrays' as EBarrays_2.44.0.zip
* DONE (EBarrays)
In R CMD INSTALL
In R CMD INSTALL
* installing to library 'C:/Users/biocbuild/bbs-3.7-bioc/R/library'
package 'EBarrays' successfully unpacked and MD5 sums checked
In R CMD INSTALL

Tests output

EBarrays.Rcheck/tests_i386/test.Rout


R version 3.5.1 Patched (2018-07-24 r75005) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: i386-w64-mingw32/i386 (32-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(EBarrays)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: lattice
> demo(ebarrays)


	demo(ebarrays)
	---- ˜˜˜˜˜˜˜˜

> library(EBarrays)

> ## EM algorithm 
> ## Lognormal-Normal Demo
> 
> ## mu10,sigma2,tau are parameters in the LNNB model; pde is the
> ## proportion of differentially expressed genes; n is the
> ## total number of genes; nr1 and nr2 are the number of replicate
> ## arrays in each group.
> 
> lnnb.sim <- function(mu10, sigmasq, tausq, pde, n, nr1, nr2)
+ {
+     de <- sample(c(TRUE, FALSE), size = n, replace = TRUE, prob = c(pde, 1 - pde))
+     x <- matrix(NA, n, nr1)
+     y <- matrix(NA, n, nr2)
+     mu1 <- rnorm(n, mu10, sqrt(tausq))
+     mu2.de <- rnorm(n, mu10, sqrt(tausq))
+     mu2 <- mu1
+     mu2[de] <- mu2.de[de]
+     for(j in 1:nr1) {
+         x[, j] <- rnorm(n, mu1, sqrt(sigmasq))
+     }
+     for(j in 1:nr2) {
+         y[, j] <- rnorm(n, mu2, sqrt(sigmasq))
+     }
+     outmat <- exp(cbind(x, y))
+     list(mu1 = mu1, mu2 = mu2, outmat = outmat, de = de)
+ }

> ## simulating data with
> ##  mu_0 = 2.33, sigma^2 = 0.1, tau^2 = 2
> ##  P(DE) = 0.2
> 
> sim.data1 <- lnnb.sim(2.33, 0.1, 2, 0.2, 2000, nr1 = 3, nr2 = 3)

> de.true1 <- sim.data1$de ## true indicators of differential expression

> sim.data2 <- lnnb.sim(1.33, 0.01, 2, 0.2, 2000, nr1 = 3, nr2 = 3)

> de.true2 <- sim.data2$de ## true indicators of differential expression

> testdata <- rbind(sim.data1$outmat,sim.data2$outmat)

> hypotheses <- ebPatterns(c("1 1 1 1 1 1", "1 1 1 2 2 2")) 

> em.out <- emfit(testdata, family = "LNN", hypotheses,
+                 cluster = 1:5,
+                 type = 2,
+                 verbose = TRUE,
+                 num.iter = 10)

 Checking for negative entries...
 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  0.46 seconds user time

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  1.10 seconds user time

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  1.61 seconds user time

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  2.40 seconds user time

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  3.10 seconds user time

> em.out

 EB model fit 
	 Family: LNN ( Lognormal-Normal )

 Model parameter estimates:

             mu_0    sigma.2  tao_0.2
Cluster 1 2.34480 0.09857423 1.944420
Cluster 2 1.39497 0.01017189 1.978711

 Estimated mixing proportions:

          Pattern.1  Pattern.2
Cluster 1 0.3931049 0.10415603
Cluster 2 0.4057305 0.09700848

> post.out <- postprob(em.out, testdata)

> table(post.out$pattern[, 2] > .5, c(de.true1,de.true2))
       
        FALSE TRUE
  FALSE  3145  175
  TRUE     35  645

> table((post.out$cluster[, 2] > .5)+1, c(rep("Cluster 1",2000),rep("Cluster 2",2000)))
   
    Cluster 1 Cluster 2
  1      1860        54
  2       140      1946

> plotMarginal(em.out,testdata)

> par(ask=TRUE)

> plotCluster(em.out,testdata)

> par(ask=FALSE)

> lnnmv.em.out <- emfit(testdata, family = "LNNMV", hypotheses, groupid=c(1,1,1,2,2,2),
+                 verbose = TRUE,
+                 num.iter = 10,
+                 p.init = c(0.95, 0.05))

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  1.42 seconds user time

> lnnmv.em.out

 EB model fit 
	 Family: LNNMV ( Lognormal-Normal with modified variances )

 Model parameter estimates:

      mu_0  tao_0.2
1 1.873206 2.185141

 Estimated mixing proportions:

       Pattern.1 Pattern.2
p.temp 0.7863179 0.2136821

> post.out <- postprob(lnnmv.em.out, testdata, groupid=c(1,1,1,2,2,2))

> table(post.out$pattern[, 2] > .5, c(de.true1,de.true2))
       
        FALSE TRUE
  FALSE  3101  169
  TRUE     79  651
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> 
> proc.time()
   user  system elapsed 
  12.43    0.14   12.56

EBarrays.Rcheck/tests_x64/test.Rout


R version 3.5.1 Patched (2018-07-24 r75005) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(EBarrays)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: lattice
> demo(ebarrays)


	demo(ebarrays)
	---- ˜˜˜˜˜˜˜˜

> library(EBarrays)

> ## EM algorithm 
> ## Lognormal-Normal Demo
> 
> ## mu10,sigma2,tau are parameters in the LNNB model; pde is the
> ## proportion of differentially expressed genes; n is the
> ## total number of genes; nr1 and nr2 are the number of replicate
> ## arrays in each group.
> 
> lnnb.sim <- function(mu10, sigmasq, tausq, pde, n, nr1, nr2)
+ {
+     de <- sample(c(TRUE, FALSE), size = n, replace = TRUE, prob = c(pde, 1 - pde))
+     x <- matrix(NA, n, nr1)
+     y <- matrix(NA, n, nr2)
+     mu1 <- rnorm(n, mu10, sqrt(tausq))
+     mu2.de <- rnorm(n, mu10, sqrt(tausq))
+     mu2 <- mu1
+     mu2[de] <- mu2.de[de]
+     for(j in 1:nr1) {
+         x[, j] <- rnorm(n, mu1, sqrt(sigmasq))
+     }
+     for(j in 1:nr2) {
+         y[, j] <- rnorm(n, mu2, sqrt(sigmasq))
+     }
+     outmat <- exp(cbind(x, y))
+     list(mu1 = mu1, mu2 = mu2, outmat = outmat, de = de)
+ }

> ## simulating data with
> ##  mu_0 = 2.33, sigma^2 = 0.1, tau^2 = 2
> ##  P(DE) = 0.2
> 
> sim.data1 <- lnnb.sim(2.33, 0.1, 2, 0.2, 2000, nr1 = 3, nr2 = 3)

> de.true1 <- sim.data1$de ## true indicators of differential expression

> sim.data2 <- lnnb.sim(1.33, 0.01, 2, 0.2, 2000, nr1 = 3, nr2 = 3)

> de.true2 <- sim.data2$de ## true indicators of differential expression

> testdata <- rbind(sim.data1$outmat,sim.data2$outmat)

> hypotheses <- ebPatterns(c("1 1 1 1 1 1", "1 1 1 2 2 2")) 

> em.out <- emfit(testdata, family = "LNN", hypotheses,
+                 cluster = 1:5,
+                 type = 2,
+                 verbose = TRUE,
+                 num.iter = 10)

 Checking for negative entries...
 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  0.50 seconds user time

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  1.26 seconds user time

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  1.91 seconds user time

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  2.53 seconds user time

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  3.84 seconds user time

> em.out

 EB model fit 
	 Family: LNN ( Lognormal-Normal )

 Model parameter estimates:

              mu_0    sigma.2  tao_0.2
Cluster 1 1.343149 0.01014914 1.943018
Cluster 2 2.311481 0.10027353 2.092340

 Estimated mixing proportions:

          Pattern.1  Pattern.2
Cluster 1 0.4142398 0.08896789
Cluster 2 0.4068071 0.08998515

> post.out <- postprob(em.out, testdata)

> table(post.out$pattern[, 2] > .5, c(de.true1,de.true2))
       
        FALSE TRUE
  FALSE  3236  158
  TRUE     33  573

> table((post.out$cluster[, 2] > .5)+1, c(rep("Cluster 1",2000),rep("Cluster 2",2000)))
   
    Cluster 1 Cluster 2
  1       144      1948
  2      1856        52

> plotMarginal(em.out,testdata)

> par(ask=TRUE)

> plotCluster(em.out,testdata)

> par(ask=FALSE)

> lnnmv.em.out <- emfit(testdata, family = "LNNMV", hypotheses, groupid=c(1,1,1,2,2,2),
+                 verbose = TRUE,
+                 num.iter = 10,
+                 p.init = c(0.95, 0.05))

 Checking for negative entries...
 Generating summary statistics for patterns. 
 This may take a few seconds...

 Starting EM iterations (total 10 ).
 This may take a while

	 Starting iteration 1 ...
	 Starting iteration 2 ...
	 Starting iteration 3 ...
	 Starting iteration 4 ...
	 Starting iteration 5 ...
	 Starting iteration 6 ...
	 Starting iteration 7 ...
	 Starting iteration 8 ...
	 Starting iteration 9 ...
	 Starting iteration 10 ...


 Fit used  1.55 seconds user time

> lnnmv.em.out

 EB model fit 
	 Family: LNNMV ( Lognormal-Normal with modified variances )

 Model parameter estimates:

      mu_0  tao_0.2
1 1.829054 2.247482

 Estimated mixing proportions:

       Pattern.1 Pattern.2
p.temp 0.8027559 0.1972441

> post.out <- postprob(lnnmv.em.out, testdata, groupid=c(1,1,1,2,2,2))

> table(post.out$pattern[, 2] > .5, c(de.true1,de.true2))
       
        FALSE TRUE
  FALSE  3190  141
  TRUE     79  590
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> 
> proc.time()
   user  system elapsed 
  14.62    0.07   14.68

Example timings

EBarrays.Rcheck/examples_i386/EBarrays-Ex.timings

nameusersystemelapsed
crit.fun3.930.073.98
ebarraysFamily-class000
emfit0.170.000.17
gould0.020.000.01
postprob0.190.000.19
utilities000

EBarrays.Rcheck/examples_x64/EBarrays-Ex.timings

nameusersystemelapsed
crit.fun4.360.044.41
ebarraysFamily-class0.020.000.01
emfit0.170.020.19
gould000
postprob0.170.010.19
utilities000