Last updated on 2019-11-26 00:52:05 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.5-4 | 141.89 | 299.91 | 441.80 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 1.5-4 | 123.70 | 213.16 | 336.86 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.5-4 | 551.76 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 1.5-4 | 590.76 | NOTE | |||
| r-devel-windows-ix86+x86_64 | 1.5-4 | 311.00 | 504.00 | 815.00 | NOTE | |
| r-devel-windows-ix86+x86_64-gcc8 | 1.5-4 | 222.00 | 388.00 | 610.00 | NOTE | |
| r-patched-linux-x86_64 | 1.5-4 | 123.28 | 330.12 | 453.40 | NOTE | |
| r-patched-solaris-x86 | 1.5-4 | 614.00 | NOTE | |||
| r-release-linux-x86_64 | 1.5-4 | 130.74 | 331.16 | 461.90 | NOTE | |
| r-release-windows-ix86+x86_64 | 1.5-4 | 278.00 | 513.00 | 791.00 | NOTE | |
| r-release-osx-x86_64 | 1.5-4 | NOTE | ||||
| r-oldrel-windows-ix86+x86_64 | 1.5-4 | 207.00 | 357.00 | 564.00 | NOTE | |
| r-oldrel-osx-x86_64 | 1.5-4 | NOTE |
Version: 1.5-4
Check: for GNU extensions in Makefiles
Result: NOTE
GNU make is a SystemRequirements.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64
Version: 1.5-4
Check: examples
Result: ERROR
Running examples in 'RBesT-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: gMAP
> ### Title: Meta-Analytic-Predictive Analysis for Generalized Linear Models
> ### Aliases: gMAP print.gMAP fitted.gMAP coef.gMAP as.matrix.gMAP
> ### summary.gMAP
>
> ### ** Examples
>
> ## Setting up dummy sampling for fast execution of example
> ## Please use 4 chains and 20x more warmup & iter in practice
> .user_mc_options <- options(RBesT.MC.warmup=50, RBesT.MC.iter=100,
+ RBesT.MC.chains=2, RBesT.MC.thin=1)
>
> # Binary data example 1
>
> # Mean response rate is ~0.25. For binary endpoints
> # a conservative choice for tau is a HalfNormal(0,1) as long as
> # the mean response rate is in the range of 0.2 to 0.8. For
> # very small or large rates consider the n_infinity approach
> # illustrated below.
> # for exact reproducible results, the seed must be set
> set.seed(34563)
> map_AS <- gMAP(cbind(r, n-r) ~ 1 | study,
+ family=binomial,
+ data=AS,
+ tau.dist="HalfNormal", tau.prior=1,
+ beta.prior=2)
Assuming default prior location for beta: 0
Warning: The largest R-hat is 1.11, indicating chains have not mixed.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#r-hat
Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#bulk-ess
Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#tail-ess
Warning in gMAP(cbind(r, n - r) ~ 1 | study, family = binomial, data = AS, :
Maximal Rhat > 1.1. Consider increasing RBesT.MC.warmup MCMC parameter.
Final MCMC sample equivalent to less than 1000 independent draws.
Please consider increasing the MCMC simulation size.
> print(map_AS)
Generalized Meta Analytic Predictive Prior Analysis
Call: gMAP(formula = cbind(r, n - r) ~ 1 | study, family = binomial,
data = AS, tau.dist = "HalfNormal", tau.prior = 1, beta.prior = 2)
Exchangeability tau strata: 1
Prediction tau stratum : 1
Maximal Rhat : 1.11
Between-trial heterogeneity of tau prediction stratum
mean sd 2.5% 50% 97.5%
0.370 0.163 0.110 0.352 0.764
MAP Prior MCMC sample
mean sd 2.5% 50% 97.5%
0.2580 0.0817 0.1230 0.2510 0.4460
>
> # obtain numerical summaries
> map_sum <- summary(map_AS)
> print(map_sum)
Heterogeneity parameter tau per stratum:
mean sd 2.5% 50% 97.5%
tau[1] 0.37 0.163 0.11 0.352 0.764
Regression coefficients:
mean sd 2.5% 50% 97.5%
(Intercept) -1.12 0.178 -1.47 -1.11 -0.767
Mean estimate MCMC sample:
mean sd 2.5% 50% 97.5%
theta_resp 0.248 0.033 0.187 0.247 0.317
MAP Prior MCMC sample:
mean sd 2.5% 50% 97.5%
theta_resp_pred 0.258 0.0817 0.123 0.251 0.446
> names(map_sum)
[1] "tau" "beta" "theta.pred" "theta"
> # [1] "tau" "beta" "theta.pred" "theta"
> map_sum$theta.pred
mean sd 2.5% 50% 97.5%
theta_resp_pred 0.2576768 0.08166927 0.1232554 0.2508299 0.4464658
>
>
> # obtain shrinkage estimates
> fitted(map_AS)
mean sd 2.5% 50% 97.5%
Study 1 0.2245230 0.03009877 0.16467408 0.2255518 0.2698386
Study 2 0.2600974 0.05160094 0.17318985 0.2610201 0.3745415
Study 3 0.3157218 0.06628311 0.21188389 0.3041774 0.4656744
Study 4 0.2440305 0.04812868 0.15154707 0.2442546 0.3333963
Study 5 0.2681039 0.03179363 0.21285005 0.2633981 0.3412085
Study 6 0.2670423 0.05109495 0.19112391 0.2609730 0.3660353
Study 7 0.1704818 0.04185255 0.08821842 0.1727647 0.2466163
Study 8 0.2649455 0.04246509 0.20001270 0.2574109 0.3462487
>
> # regression coefficients
> coef(map_AS)
mean sd 2.5% 50% 97.5%
(Intercept) -1.11748 0.1782488 -1.468582 -1.113787 -0.7667301
>
> # finally fit MAP prior with parametric mixture
> map_mix <- mixfit(map_AS, Nc=2)
> plot(map_mix)$mix
Error in parameter_names.array(x) : is_3d_array(x) is not TRUE
Calls: plot ... parameter_names -> parameter_names.array -> stopifnot
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 1.5-4
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
...
--- re-building 'PoS_codata.Rmd' using rmarkdown
Quitting from lines 358-375 (PoS_codata.Rmd)
Error: processing vignette 'PoS_codata.Rmd' failed with diagnostics:
is_3d_array(x) is not TRUE
--- failed re-building 'PoS_codata.Rmd'
--- re-building 'PoS_interim.Rmd' using rmarkdown
--- finished re-building 'PoS_interim.Rmd'
--- re-building 'customizing_plots.Rmd' using rmarkdown
Loading required package: Rcpp
This is RBesT version 1.5.4
This is bayesplot version 1.7.0
- Online documentation and vignettes at mc-stan.org/bayesplot
- bayesplot theme set to bayesplot::theme_default()
* Does _not_ affect other ggplot2 plots
* See ?bayesplot_theme_set for details on theme setting
Warning: The largest R-hat is 1.14, indicating chains have not mixed.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#r-hat
Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#bulk-ess
Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#tail-ess
Warning in gMAP(cbind(y, y.se) ~ 1 | study, family = gaussian, data = transform(crohn, :
Maximal Rhat > 1.1. Consider increasing RBesT.MC.warmup MCMC parameter.
Final MCMC sample equivalent to less than 1000 independent draws.
Please consider increasing the MCMC simulation size.
--- finished re-building 'customizing_plots.Rmd'
--- re-building 'introduction.Rmd' using rmarkdown
Quitting from lines 136-139 (introduction.Rmd)
Error: processing vignette 'introduction.Rmd' failed with diagnostics:
is_3d_array(x) is not TRUE
--- failed re-building 'introduction.Rmd'
--- re-building 'introduction_normal.Rmd' using rmarkdown
Quitting from lines 119-123 (introduction_normal.Rmd)
Error: processing vignette 'introduction_normal.Rmd' failed with diagnostics:
is_3d_array(x) is not TRUE
--- failed re-building 'introduction_normal.Rmd'
--- re-building 'robustMAP.Rmd' using rmarkdown
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Warning in calc_loc(mix, "mode") :
Detected multiple modes.
The ESS is determined for the largest mode, but ESS concept is ill-defined for multi-modal distributions.
Quitting from lines 290-313 (robustMAP.Rmd)
Error: processing vignette 'robustMAP.Rmd' failed with diagnostics:
is_3d_array(x) is not TRUE
--- failed re-building 'robustMAP.Rmd'
--- re-building 'variances_MAP.Rmd' using rmarkdown
Quitting from lines 142-153 (variances_MAP.Rmd)
Error: processing vignette 'variances_MAP.Rmd' failed with diagnostics:
is_3d_array(x) is not TRUE
--- failed re-building 'variances_MAP.Rmd'
SUMMARY: processing the following files failed:
'PoS_codata.Rmd' 'introduction.Rmd' 'introduction_normal.Rmd'
'robustMAP.Rmd' 'variances_MAP.Rmd'
Error: Vignette re-building failed.
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 1.5-4
Check: installed package size
Result: NOTE
installed size is 32.0Mb
sub-directories of 1Mb or more:
doc 2.7Mb
libs 28.2Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8, r-patched-solaris-x86, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64