Running examples in ‘BayesVarSel-Ex.R’ failed (not sure why)

Don’t get what goes wrong here:

* using log directory ‘/opt/local/var/macports/build/_opt_PPCSnowLeopardPorts_R_R-BayesVarSel/R-BayesVarSel/work/BayesVarSel/BayesVarSel.Rcheck’
* using R version 4.2.3 (2023-03-15)
* using platform: powerpc-apple-darwin10.8.0 (32-bit)
* using session charset: UTF-8
* checking for file ‘BayesVarSel/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘BayesVarSel’ version ‘2.2.5’
* package encoding: UTF-8
* 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 executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BayesVarSel’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* 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
* 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* 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 ... OK
* 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 ... NOTE
  Note: found 385 marked UTF-8 strings
* checking LazyData ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking use of PKG_*FLAGS in Makefiles ... OK
* checking compiled code ... OK
* checking examples ... ERROR
Running examples in ‘BayesVarSel-Ex.R’ failed
The error most likely occurred in:

> ### Name: BayesVarSel-package
> ### Title: Bayes Factors, Model Choice And Variable Selection In Linear
> ###   Models
> ### Aliases: BayesVarSel-package BayesVarSel
> ### Keywords: package
> 
> ### ** Examples
> 
> demo(BayesVarSel.Hald)

    demo(BayesVarSel.Hald)
    ---- ~~~~~~~~~~~~~~~~

> #read Hald data
> data(Hald)

> #run the main function: (in this small example we keep all models)
> hald.Bvs<- Bvs(formula="y~x1+x2+x3+x4", data=Hald, n.keep=16)
Info. . . .
Most complex model has 5 covariates
From those 1 is fixed and we should select from the remaining 4 
x1, x2, x3, x4
The problem has a total of 16 competing models
Of these, the  16 most probable (a posteriori) are kept
Working on the problem...please wait.
* checking PDF version of manual ... WARNING
LaTeX errors when creating PDF version.
This typically indicates Rd problems.
* checking PDF version of manual without index ... ERROR
Re-running with no redirection of stdout/stderr.
* DONE
Status: 2 ERRORs, 1 WARNING, 1 NOTE

R version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: powerpc-apple-darwin10.8.0 (32-bit)

> pkgname <- "BayesVarSel"
> source(file.path(R.home("share"), "R", "examples-header.R"))
> options(warn = 1)
> library('BayesVarSel')
Loading required package: MASS
Loading required package: mvtnorm
Loading required package: parallel
> 
> base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
> base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv')
> cleanEx()
> nameEx("BMAcoeff")
> ### * BMAcoeff
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: BMAcoeff
> ### Title: Bayesian Model Averaged estimations of regression coefficients
> ### Aliases: BMAcoeff
> 
> ### ** Examples
> 
> 
> ## Not run: 
> ##D 
> ##D #Analysis of Crime Data
> ##D #load data
> ##D data(UScrime)
> ##D 
> ##D crime.Bvs<- Bvs(formula= y ~ ., data=UScrime, n.keep=1000)
> ##D crime.Bvs.BMA<- BMAcoeff(crime.Bvs, n.sim=10000)
> ##D #the best 1000 models are used in the mixture
> ##D 
> ##D #We could force all  possible models to be included in the mixture
> ##D crime.Bvs.all<- Bvs(formula= y ~ ., data=UScrime, n.keep=2^15)
> ##D crime.Bvs.BMA<- BMAcoeff(crime.Bvs.all, n.sim=10000)
> ##D #(much slower as this implies ordering many more models...)
> ##D 
> ##D #With the Gibbs algorithms:
> ##D data(Ozone35)
> ##D 
> ##D Oz35.GibbsBvs<- GibbsBvs(formula= y ~ ., data=Ozone35, prior.betas="gZellner",
> ##D prior.models="Constant", n.iter=10000, init.model="Full", n.burnin=100,
> ##D time.test = FALSE)
> ##D Oz35.GibbsBvs.BMA<- BMAcoeff(Oz35.GibbsBvs, n.sim=10000)
> ##D 
> ##D 
> ## End(Not run)
> 
> 
> 
> 
> cleanEx()
> nameEx("BayesVarSel-package")
> ### * BayesVarSel-package
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: BayesVarSel-package
> ### Title: Bayes Factors, Model Choice And Variable Selection In Linear
> ###   Models
> ### Aliases: BayesVarSel-package BayesVarSel
> ### Keywords: package
> 
> ### ** Examples
> 
> demo(BayesVarSel.Hald)

    demo(BayesVarSel.Hald)
    ---- ~~~~~~~~~~~~~~~~

> #read Hald data
> data(Hald)

> #run the main function: (in this small example we keep all models)
> hald.Bvs<- Bvs(formula="y~x1+x2+x3+x4", data=Hald, n.keep=16)
Info. . . .
Most complex model has 5 covariates
From those 1 is fixed and we should select from the remaining 4 
x1, x2, x3, x4
The problem has a total of 16 competing models
Of these, the  16 most probable (a posteriori) are kept
Working on the problem...please wait.

comodin19 / BayesVarSel

Running examples in ‘BayesVarSel-Ex.R’ failed (not sure why) #47