- using R version 4.6.1 (2026-06-24)
- using platform: x86_64-pc-linux-gnu
- R was compiled by
gcc-16 (Debian 16.2.0-3) 16.2.0
GNU Fortran (Debian 16.2.0-3) 16.2.0
- running under: Debian GNU/Linux forky/sid
- using session charset: UTF-8
* current time: 2026-10-03 22:07:42 UTC
- checking for file ‘spsurv/DESCRIPTION’ ... OK
- checking extension type ... Package
- this is package ‘spsurv’ version ‘1.1.0’
- 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 ‘spsurv’ can be installed ... OK
See the install log for details.
- used C++ compiler: ‘g++-16 (Debian 16.2.0-3) 16.2.0’
- checking C++ specification ... INFO
specified C++17
- checking package directory ... OK
- checking for future file timestamps ... OK
- checking ‘build’ 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 code files for non-ASCII characters ... OK
- checking R files for syntax errors ... OK
- checking whether the package can be loaded ... [6s/7s] OK
- checking whether the package can be loaded with stated dependencies ... [6s/8s] OK
- checking whether the package can be unloaded cleanly ... [6s/8s] OK
- checking whether the namespace can be loaded with stated dependencies ... [6s/7s] OK
- checking whether the namespace can be unloaded cleanly ... [6s/9s] OK
- checking loading without being on the library search path ... [6s/7s] OK
- checking whether startup messages can be suppressed ... [6s/6s] OK
- checking use of S3 registration ... 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 ... [37s/46s] OK
- checking Rd files ... [1s/1s] OK
- checking Rd metadata ... OK
- checking Rd line widths ... 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 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 ... INFO
GNU make is a SystemRequirements.
- checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
- checking use of PKG_*FLAGS in Makefiles ... OK
- checking use of SHLIB_OPENMP_*FLAGS in Makefiles ... OK
- checking pragmas in C/C++ headers and code ... OK
- checking compilation flags used ... OK
- checking compiled code ... OK
- checking installed files from ‘inst/doc’ ... OK
- checking files in ‘vignettes’ ... OK
- checking examples ... [9s/12s] OK
- checking for unstated dependencies in ‘tests’ ... OK
- checking tests ... [46s/61s] ERROR
Running ‘testthat.R’ [46s/61s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(parsnip)
> library(generics)
Attaching package: 'generics'
The following objects are masked from 'package:base':
as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
setequal, union
> library(spsurv)
Loading required package: survival
Loading required package: coda
> veteran <- survival::veteran
>
> test_check("spsurv")
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9.6e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.96 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
Chain 1: Iteration: 4 / 10 [ 40%] (Warmup)
Chain 1: Iteration: 5 / 10 [ 50%] (Warmup)
Chain 1: Iteration: 6 / 10 [ 60%] (Sampling)
Chain 1: Iteration: 7 / 10 [ 70%] (Sampling)
Chain 1: Iteration: 8 / 10 [ 80%] (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.009 seconds (Warm-up)
Chain 1: 0.004 seconds (Sampling)
Chain 1: 0.013 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.0001 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
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Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.008 seconds (Warm-up)
Chain 1: 0.002 seconds (Sampling)
Chain 1: 0.01 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000584 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 5.84 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
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Chain 1: Iteration: 8 / 10 [ 80%] (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.031 seconds (Warm-up)
Chain 1: 0.094 seconds (Sampling)
Chain 1: 0.125 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9.2e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.92 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
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Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.013 seconds (Warm-up)
Chain 1: 0.006 seconds (Sampling)
Chain 1: 0.019 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.5e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.85 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
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Chain 1: Iteration: 8 / 10 [ 80%] (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.014 seconds (Warm-up)
Chain 1: 0.013 seconds (Sampling)
Chain 1: 0.027 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 7.6e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.76 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
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Chain 1: Iteration: 8 / 10 [ 80%] (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.009 seconds (Warm-up)
Chain 1: 0.008 seconds (Sampling)
Chain 1: 0.017 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 7.7e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.77 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
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Chain 1: Iteration: 8 / 10 [ 80%] (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.011 seconds (Warm-up)
Chain 1: 0.016 seconds (Sampling)
Chain 1: 0.027 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.2e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.82 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
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Chain 1: Iteration: 8 / 10 [ 80%] (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.009 seconds (Warm-up)
Chain 1: 0.001 seconds (Sampling)
Chain 1: 0.01 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.6e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.86 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
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Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.012 seconds (Warm-up)
Chain 1: 0.023 seconds (Sampling)
Chain 1: 0.035 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.0001 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
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Chain 1: Iteration: 8 / 10 [ 80%] (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.018 seconds (Warm-up)
Chain 1: 0.019 seconds (Sampling)
Chain 1: 0.037 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.8 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
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Chain 1: Iteration: 8 / 10 [ 80%] (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.045 seconds (Warm-up)
Chain 1: 0.056 seconds (Sampling)
Chain 1: 0.101 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9.6e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.96 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
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Chain 1: Iteration: 8 / 10 [ 80%] (Sampling)
Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.011 seconds (Warm-up)
Chain 1: 0.004 seconds (Sampling)
Chain 1: 0.015 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000749 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 7.49 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
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Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.011 seconds (Warm-up)
Chain 1: 0.018 seconds (Sampling)
Chain 1: 0.029 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000103 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.03 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
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Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.009 seconds (Warm-up)
Chain 1: 0.001 seconds (Sampling)
Chain 1: 0.01 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9.1e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.91 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
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Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.005 seconds (Warm-up)
Chain 1: 0.012 seconds (Sampling)
Chain 1: 0.017 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000114 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.14 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
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Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.006 seconds (Warm-up)
Chain 1: 0.01 seconds (Sampling)
Chain 1: 0.016 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.00012 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.2 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
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Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.048 seconds (Warm-up)
Chain 1: 0.016 seconds (Sampling)
Chain 1: 0.064 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.9e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.89 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
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Chain 1: Iteration: 9 / 10 [ 90%] (Sampling)
Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.017 seconds (Warm-up)
Chain 1: 0.05 seconds (Sampling)
Chain 1: 0.067 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9.3e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.93 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
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Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.01 seconds (Warm-up)
Chain 1: 0.011 seconds (Sampling)
Chain 1: 0.021 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000808 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 8.08 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
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Chain 1:
Chain 1: Elapsed Time: 0.093 seconds (Warm-up)
Chain 1: 0.123 seconds (Sampling)
Chain 1: 0.216 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.7e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.87 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
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Chain 1:
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Chain 1: 0.001 seconds (Sampling)
Chain 1: 0.006 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.9 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
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Chain 1:
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Chain 1: 0.014 seconds (Sampling)
Chain 1: 0.026 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.8e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.88 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
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Chain 1:
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Chain 1: 0.011 seconds (Sampling)
Chain 1: 0.027 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000115 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.15 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
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Chain 1:
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Chain 1:
Chain 1: Elapsed Time: 0.027 seconds (Warm-up)
Chain 1: 0.017 seconds (Sampling)
Chain 1: 0.044 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.005322 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 53.22 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
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Chain 1:
Chain 1: Elapsed Time: 0.016 seconds (Warm-up)
Chain 1: 0.001 seconds (Sampling)
Chain 1: 0.017 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000132 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.32 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
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Chain 1:
Chain 1: Elapsed Time: 0.05 seconds (Warm-up)
Chain 1: 0.019 seconds (Sampling)
Chain 1: 0.069 seconds (Total)
Chain 1:
Saving _problems/test-interval-44.R
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000106 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.06 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
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Chain 1:
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Chain 1:
Chain 1: Elapsed Time: 0.016 seconds (Warm-up)
Chain 1: 0.016 seconds (Sampling)
Chain 1: 0.032 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9.7e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.97 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: There aren't enough warmup iterations to fit the
Chain 1: three stages of adaptation as currently configured.
Chain 1: Reducing each adaptation stage to 15%/75%/10% of
Chain 1: the given number of warmup iterations:
Chain 1: init_buffer = 3
Chain 1: adapt_window = 20
Chain 1: term_buffer = 2
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Chain 1:
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Chain 1: 0.757 seconds (Sampling)
Chain 1: 1.523 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.002937 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 29.37 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
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Chain 1:
Chain 1: Elapsed Time: 0.025 seconds (Warm-up)
Chain 1: 0.015 seconds (Sampling)
Chain 1: 0.04 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000172 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.72 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
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Chain 1:
Chain 1: Elapsed Time: 0.011 seconds (Warm-up)
Chain 1: 0.011 seconds (Sampling)
Chain 1: 0.022 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.1e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.81 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
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Chain 1: 0.008 seconds (Sampling)
Chain 1: 0.021 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.8e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.88 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
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Chain 1:
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Chain 1: 0.005 seconds (Sampling)
Chain 1: 0.012 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000547 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 5.47 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
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Chain 1:
Chain 1: Elapsed Time: 0.668 seconds (Warm-up)
Chain 1: 0.226 seconds (Sampling)
Chain 1: 0.894 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 7.9e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.79 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
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Chain 1:
Chain 1: Elapsed Time: 0.012 seconds (Warm-up)
Chain 1: 0.001 seconds (Sampling)
Chain 1: 0.013 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000126 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.26 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
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Chain 1:
Chain 1: Elapsed Time: 0.022 seconds (Warm-up)
Chain 1: 0.031 seconds (Sampling)
Chain 1: 0.053 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.8 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
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Chain 1:
Chain 1: Elapsed Time: 0.009 seconds (Warm-up)
Chain 1: 0.005 seconds (Sampling)
Chain 1: 0.014 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9.5e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.95 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: There aren't enough warmup iterations to fit the
Chain 1: three stages of adaptation as currently configured.
Chain 1: Reducing each adaptation stage to 15%/75%/10% of
Chain 1: the given number of warmup iterations:
Chain 1: init_buffer = 3
Chain 1: adapt_window = 15
Chain 1: term_buffer = 2
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Chain 1:
Chain 1: Elapsed Time: 0.124 seconds (Warm-up)
Chain 1: 0.093 seconds (Sampling)
Chain 1: 0.217 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9.2e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.92 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
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Chain 1:
Chain 1: Elapsed Time: 0.012 seconds (Warm-up)
Chain 1: 0.004 seconds (Sampling)
Chain 1: 0.016 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 7.7e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.77 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
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Chain 1:
Chain 1: Elapsed Time: 0.059 seconds (Warm-up)
Chain 1: 0.03 seconds (Sampling)
Chain 1: 0.089 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9.1e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.91 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
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Chain 1:
Chain 1: Elapsed Time: 0.035 seconds (Warm-up)
Chain 1: 0.077 seconds (Sampling)
Chain 1: 0.112 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 9e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.9 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
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Chain 1:
Chain 1: Elapsed Time: 0.009 seconds (Warm-up)
Chain 1: 0.012 seconds (Sampling)
Chain 1: 0.021 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.7e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.87 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
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Chain 1:
Call:
bpph(formula = Surv(time, status) ~ 1, data = veteran, approach = "mle",
model = "ph")
log(gamma) gamma
gamma[1] -0.029 1.0
gamma[2] -1.286 0.3
gamma[3] -0.052 0.9
gamma[4] -10.829 0.0
gamma[5] -22.986 0.0
gamma[6] 0.620 1.9
gamma[7] -28.931 0.0
gamma[8] -74.954 0.0
gamma[9] -66.824 0.0
gamma[10] -118.873 0.0
gamma[11] -56.147 0.0
gamma[12] 0.054 1.1
Loglik(model)= -744 Loglik(baseline only)= -744
n= 137, number of events= 128Call:
bpph(formula = Surv(time, status) ~ 1, data = veteran, approach = "mle",
model = "ph")
log(gamma) gamma
gamma[1] -0.029 1.0
gamma[2] -1.286 0.3
gamma[3] -0.052 0.9
gamma[4] -10.829 0.0
gamma[5] -22.986 0.0
gamma[6] 0.620 1.9
gamma[7] -28.931 0.0
gamma[8] -74.954 0.0
gamma[9] -66.824 0.0
gamma[10] -118.873 0.0
gamma[11] -56.147 0.0
gamma[12] 0.054 1.1
Loglik(model)= -744 Loglik(baseline only)= -744
n= 137, number of events= 128
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 7.1e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.71 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
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Chain 1: 0.004 seconds (Total)
Chain 1:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 2).
Chain 2:
Chain 2: Gradient evaluation took 8.4e-05 seconds
Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.84 seconds.
Chain 2: Adjust your expectations accordingly!
Chain 2:
Chain 2:
Chain 2: WARNING: No variance estimation is
Chain 2: performed for num_warmup < 20
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Chain 2: 0.019 seconds (Total)
Chain 2:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 3).
Chain 3:
Chain 3: Gradient evaluation took 4.6e-05 seconds
Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.46 seconds.
Chain 3: Adjust your expectations accordingly!
Chain 3:
Chain 3:
Chain 3: WARNING: No variance estimation is
Chain 3: performed for num_warmup < 20
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Chain 3:
Chain 3: Elapsed Time: 0.009 seconds (Warm-up)
Chain 3: 0.004 seconds (Sampling)
Chain 3: 0.013 seconds (Total)
Chain 3:
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 4).
Chain 4:
Chain 4: Gradient evaluation took 4.6e-05 seconds
Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0.46 seconds.
Chain 4: Adjust your expectations accordingly!
Chain 4:
Chain 4:
Chain 4: WARNING: No variance estimation is
Chain 4: performed for num_warmup < 20
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Chain 4:
Chain 4: Elapsed Time: 0.005 seconds (Warm-up)
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Chain 4:
Call:
bpph(formula = Surv(time, status) ~ 1, data = veteran, approach = "bayes",
iter = 10, cores = 1, model = "ph")
mean(bp) mode(bp) median(bp) mean(log(bp)) sd(bp)
gamma[1] 1.049 1.060 1.052 0.031 0.2
gamma[2] 0.293 0.083 0.137 -2.194 0.3
gamma[3] 0.434 0.192 0.274 -1.304 0.4
gamma[4] 0.500 0.249 0.421 -1.210 0.4
gamma[5] 0.144 0.049 0.117 -2.423 0.1
gamma[6] 0.767 0.333 0.512 -1.104 0.7
gamma[7] 0.664 0.141 0.295 -1.477 0.8
gamma[8] 0.388 0.078 0.070 -2.088 0.6
gamma[9] 0.266 0.058 0.146 -2.774 0.4
gamma[10] 0.157 0.012 0.019 -3.967 0.3
gamma[11] 0.153 0.050 0.107 -2.947 0.2
gamma[12] 1.179 0.864 0.970 -0.024 0.8
Deviance criterion= 1502 Watanabe–Akaike criterion= -750
Log pseudo-marginal lik= -750
n= 137, number of events= 128Call:
bpph(formula = Surv(time, status) ~ 1, data = veteran, approach = "bayes",
iter = 10, cores = 1, model = "ph")
mean(bp) mode(bp) median(bp) mean(log(bp)) sd(bp)
gamma[1] 1.049 1.060 1.052 0.031 0.2
gamma[2] 0.293 0.083 0.137 -2.194 0.3
gamma[3] 0.434 0.192 0.274 -1.304 0.4
gamma[4] 0.500 0.249 0.421 -1.210 0.4
gamma[5] 0.144 0.049 0.117 -2.423 0.1
gamma[6] 0.767 0.333 0.512 -1.104 0.7
gamma[7] 0.664 0.141 0.295 -1.477 0.8
gamma[8] 0.388 0.078 0.070 -2.088 0.6
gamma[9] 0.266 0.058 0.146 -2.774 0.4
gamma[10] 0.157 0.012 0.019 -3.967 0.3
gamma[11] 0.153 0.050 0.107 -2.947 0.2
gamma[12] 1.179 0.864 0.970 -0.024 0.8
Deviance criterion= 1502 Watanabe–Akaike criterion= -750
Log pseudo-marginal lik= -750
n= 137, number of events= 128Call:
bpph(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "mle", model = "ph")
Bernstein PH model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error z value Pr(>|z|)
karno -0.0310 -0.0411 -0.0209 0.0052 -6.0 2e-09
factor(celltype)smallcell 0.7355 0.2401 1.2309 0.2528 2.9 0.004
factor(celltype)adeno 1.1391 0.5641 1.7141 0.2934 3.9 1e-04
factor(celltype)large 0.3292 -0.2118 0.8702 0.2760 1.2 0.233
karno ***
factor(celltype)smallcell **
factor(celltype)adeno ***
factor(celltype)large
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 0.97 0.96 1.0
factor(celltype)smallcell 2.09 1.27 3.4
factor(celltype)adeno 3.12 1.76 5.6
factor(celltype)large 1.39 0.81 2.4
---
loglik = -714 AIC = 1460
Call:
bpph(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "mle", model = "ph")
Bernstein PH model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error z value Pr(>|z|)
karno -0.0310 -0.0411 -0.0209 0.0052 -6.0 2e-09
factor(celltype)smallcell 0.7355 0.2401 1.2309 0.2528 2.9 0.004
factor(celltype)adeno 1.1391 0.5641 1.7141 0.2934 3.9 1e-04
factor(celltype)large 0.3292 -0.2118 0.8702 0.2760 1.2 0.233
karno ***
factor(celltype)smallcell **
factor(celltype)adeno ***
factor(celltype)large
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 0.97 0.96 1.0
factor(celltype)smallcell 2.09 1.27 3.4
factor(celltype)adeno 3.12 1.76 5.6
factor(celltype)large 1.39 0.81 2.4
---
loglik = -714 AIC = 1460
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000115 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.15 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
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Chain 1:
Chain 1: Elapsed Time: 0.001 seconds (Warm-up)
Chain 1: 0.038 seconds (Sampling)
Chain 1: 0.039 seconds (Total)
Chain 1:
Call:
bpph(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "bayes", iter = 10, chains = 1,
cores = 1, model = "ph")
Bayesian Bernstein PH model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error
karno -0.029 -0.040 -0.016 0.0
factor(celltype)smallcell 1.216 0.630 2.591 0.8
factor(celltype)adeno 1.564 0.880 3.343 1.0
factor(celltype)large 0.839 0.125 3.195 1.3
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 0.97 0.96 1
factor(celltype)smallcell 4.62 1.88 13
factor(celltype)adeno 8.22 2.41 28
factor(celltype)large 5.92 1.13 24
---
DIC = 10366 WAIC = -953
Call:
bpph(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "bayes", iter = 10, chains = 1,
cores = 1, model = "ph")
Bayesian Bernstein PH model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error
karno -0.029 -0.040 -0.016 0.0
factor(celltype)smallcell 1.216 0.630 2.591 0.8
factor(celltype)adeno 1.564 0.880 3.343 1.0
factor(celltype)large 0.839 0.125 3.195 1.3
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 0.97 0.96 1
factor(celltype)smallcell 4.62 1.88 13
factor(celltype)adeno 8.22 2.41 28
factor(celltype)large 5.92 1.13 24
---
DIC = 10366 WAIC = -953
Call:
bppo(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "mle", model = "po")
Bernstein PO model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error z value Pr(>|z|)
karno -0.0613 -0.0785 -0.0441 0.0088 -7.0 3e-12
factor(celltype)smallcell 1.2887 0.4317 2.1457 0.4373 2.9 0.003
factor(celltype)adeno 1.4380 0.5096 2.3664 0.4737 3.0 0.002
factor(celltype)large 0.1078 -0.8067 1.0223 0.4666 0.2 0.817
karno ***
factor(celltype)smallcell **
factor(celltype)adeno **
factor(celltype)large
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 0.94 0.92 1.0
factor(celltype)smallcell 3.63 1.54 8.5
factor(celltype)adeno 4.21 1.66 10.7
factor(celltype)large 1.11 0.45 2.8
---
loglik = -708 AIC = 1448
Call:
bppo(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "mle", model = "po")
Bernstein PO model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error z value Pr(>|z|)
karno -0.0613 -0.0785 -0.0441 0.0088 -7.0 3e-12
factor(celltype)smallcell 1.2887 0.4317 2.1457 0.4373 2.9 0.003
factor(celltype)adeno 1.4380 0.5096 2.3664 0.4737 3.0 0.002
factor(celltype)large 0.1078 -0.8067 1.0223 0.4666 0.2 0.817
karno ***
factor(celltype)smallcell **
factor(celltype)adeno **
factor(celltype)large
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 0.94 0.92 1.0
factor(celltype)smallcell 3.63 1.54 8.5
factor(celltype)adeno 4.21 1.66 10.7
factor(celltype)large 1.11 0.45 2.8
---
loglik = -708 AIC = 1448
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.00012 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.2 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
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Chain 1:
Chain 1: Elapsed Time: 0.02 seconds (Warm-up)
Chain 1: 0.013 seconds (Sampling)
Chain 1: 0.033 seconds (Total)
Chain 1:
Call:
bppo(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "bayes", iter = 10, chains = 1,
cores = 1, model = "po")
Bayesian Bernstein PO model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error
karno -0.074 -0.076 -0.067 0.0
factor(celltype)smallcell 0.931 0.661 0.999 0.2
factor(celltype)adeno 0.825 0.806 0.901 0.0
factor(celltype)large -0.462 -0.572 -0.434 0.1
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 0.93 0.93 0.9
factor(celltype)smallcell 2.56 1.94 2.7
factor(celltype)adeno 2.28 2.24 2.5
factor(celltype)large 0.63 0.56 0.6
---
DIC = 1428 WAIC = -714
Call:
bppo(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "bayes", iter = 10, chains = 1,
cores = 1, model = "po")
Bayesian Bernstein PO model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error
karno -0.074 -0.076 -0.067 0.0
factor(celltype)smallcell 0.931 0.661 0.999 0.2
factor(celltype)adeno 0.825 0.806 0.901 0.0
factor(celltype)large -0.462 -0.572 -0.434 0.1
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 0.93 0.93 0.9
factor(celltype)smallcell 2.56 1.94 2.7
factor(celltype)adeno 2.28 2.24 2.5
factor(celltype)large 0.63 0.56 0.6
---
DIC = 1428 WAIC = -714
Call:
bpaft(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "mle", model = "aft")
Bernstein AFT model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error z value Pr(>|z|)
karno 0.0348 0.0251 0.0444 0.0049 7.0 2e-12
factor(celltype)smallcell -0.7462 -1.3206 -0.1718 0.2931 -2.5 0.011
factor(celltype)adeno -0.8993 -1.4573 -0.3413 0.2847 -3.2 0.002
factor(celltype)large -0.1325 -0.6903 0.4252 0.2846 -0.5 0.641
karno ***
factor(celltype)smallcell *
factor(celltype)adeno **
factor(celltype)large
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 1.04 1.03 1.0
factor(celltype)smallcell 0.47 0.27 0.8
factor(celltype)adeno 0.41 0.23 0.7
factor(celltype)large 0.88 0.50 1.5
---
loglik = -710 AIC = 1451
Call:
bpaft(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "mle", model = "aft")
Bernstein AFT model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error z value Pr(>|z|)
karno 0.0348 0.0251 0.0444 0.0049 7.0 2e-12
factor(celltype)smallcell -0.7462 -1.3206 -0.1718 0.2931 -2.5 0.011
factor(celltype)adeno -0.8993 -1.4573 -0.3413 0.2847 -3.2 0.002
factor(celltype)large -0.1325 -0.6903 0.4252 0.2846 -0.5 0.641
karno ***
factor(celltype)smallcell *
factor(celltype)adeno **
factor(celltype)large
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 1.04 1.03 1.0
factor(celltype)smallcell 0.47 0.27 0.8
factor(celltype)adeno 0.41 0.23 0.7
factor(celltype)large 0.88 0.50 1.5
---
loglik = -710 AIC = 1451
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000668 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 6.68 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
Chain 1: Iteration: 2 / 10 [ 20%] (Warmup)
Chain 1: Iteration: 3 / 10 [ 30%] (Warmup)
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Chain 1: Iteration: 10 / 10 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.006 seconds (Warm-up)
Chain 1: 0.028 seconds (Sampling)
Chain 1: 0.034 seconds (Total)
Chain 1:
Call:
bpaft(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "bayes", iter = 10, chains = 1,
cores = 1, model = "aft")
Bayesian Bernstein AFT model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error
karno 0.043 0.039 0.048 0.0
factor(celltype)smallcell 0.233 -0.048 0.402 0.2
factor(celltype)adeno 1.075 0.745 1.276 0.3
factor(celltype)large 2.384 1.639 2.856 0.4
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 1.04 1.04 1.0
factor(celltype)smallcell 1.29 0.95 1.5
factor(celltype)adeno 3.02 2.11 3.6
factor(celltype)large 11.64 5.15 17.4
---
DIC = 1527 WAIC = -758
Call:
bpaft(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "bayes", iter = 10, chains = 1,
cores = 1, model = "aft")
Bayesian Bernstein AFT model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error
karno 0.043 0.039 0.048 0.0
factor(celltype)smallcell 0.233 -0.048 0.402 0.2
factor(celltype)adeno 1.075 0.745 1.276 0.3
factor(celltype)large 2.384 1.639 2.856 0.4
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 1.04 1.04 1.0
factor(celltype)smallcell 1.29 0.95 1.5
factor(celltype)adeno 3.02 2.11 3.6
factor(celltype)large 11.64 5.15 17.4
---
DIC = 1527 WAIC = -758
Call:
spbp.default(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "mle", model = "ph", degree = 12)
Bernstein PH model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error z value Pr(>|z|)
karno -0.0310 -0.0411 -0.0209 0.0052 -6.0 2e-09
factor(celltype)smallcell 0.7277 0.2402 1.2151 0.2487 2.9 0.003
factor(celltype)adeno 1.1328 0.5624 1.7032 0.2910 3.9 1e-04
factor(celltype)large 0.3242 -0.2137 0.8621 0.2744 1.2 0.237
karno ***
factor(celltype)smallcell **
factor(celltype)adeno ***
factor(celltype)large
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 0.97 0.96 1.0
factor(celltype)smallcell 2.07 1.27 3.4
factor(celltype)adeno 3.10 1.75 5.5
factor(celltype)large 1.38 0.81 2.4
---
loglik = -714 AIC = 1460
SAMPLING FOR MODEL 'spbp' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 8.3e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.83 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: WARNING: No variance estimation is
Chain 1: performed for num_warmup < 20
Chain 1:
Chain 1: Iteration: 1 / 10 [ 10%] (Warmup)
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Chain 1:
Chain 1: Elapsed Time: 0 seconds (Warm-up)
Chain 1: 0 seconds (Sampling)
Chain 1: 0 seconds (Total)
Chain 1:
Call:
spbp.default(formula = Surv(time, status) ~ karno + factor(celltype),
data = veteran, approach = "bayes", cores = 1, chains = 1,
iter = 10, model = "ph", degree = 12)
Bayesian Bernstein PH model:
Regression coefficients:
Estimate 2.5% 97.5% Std. Error
karno 0.024 0.024 0.024 0
factor(celltype)smallcell -0.613 -0.613 -0.613 0
factor(celltype)adeno -4.014 -4.014 -4.014 0
factor(celltype)large -2.334 -2.334 -2.334 0
Exponentiated coefficients:
Estimate 2.5% 97.5%
karno 1.025 1.025 1.0
factor(celltype)smallcell 0.542 0.542 0.5
factor(celltype)adeno 0.018 0.018 0.0
factor(celltype)large 0.097 0.097 0.1
---
DIC = 2885 WAIC = -1443
[ FAIL 1 | WARN 51 | SKIP 1 | PASS 684 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• Set SPSURV_RUN_COVERAGE=true to run coverage check (1): 'test-coverage.R:6:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-interval.R:44:3'): credint on MLE fit warns and calls confint ──
Error in `array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x), NULL) else NULL)`: 'data' must be of a vector type, was 'NULL'
Backtrace:
▆
1. ├─testthat::expect_warning(ci <- credint(fit), "not applicable") at test-interval.R:44:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. ├─spsurv::credint(fit)
7. └─spsurv:::credint.spbp(fit)
8. └─spsurv:::confint.spbp(x, level = prob)
9. ├─base::diag(as.matrix(vcov(object)))
10. ├─base::as.matrix(vcov(object))
11. └─base::as.matrix.default(vcov(object))
12. └─base::array(...)
[ FAIL 1 | WARN 51 | SKIP 1 | PASS 684 ]
Error:
! Test failures.
Execution halted
- checking for unstated dependencies in vignettes ... OK
- checking package vignettes ... OK
- checking re-building of vignette outputs ... [95s/117s] OK
- checking PDF version of manual ... [6s/8s] OK
- checking HTML version of manual ... [3s/5s] OK
- checking for non-standard things in the check directory ... OK
- DONE
Status: 1 ERROR