stnorton
commented
5 years ago Turns out this is because the 'coda' package doesn't appear to be attached with hdpGLM. If coda is attached, it's possible to work with saved model objects.
Closed stnorton closed 5 years ago
stnorton
commented
5 years ago Turns out this is because the 'coda' package doesn't appear to be attached with hdpGLM. If coda is attached, it's possible to work with saved model objects.
DiogoFerrari
commented
5 years ago Have you loaded the hdpGLM library as well? You need to load the hdpGLM library because the package contains the functions that recognize the hdpGLM object. If you only load the Rdata you saved without loading the hdpGLM library, it probably won't work.
stnorton
commented
5 years ago Yes, I should've mentioned that. If I load hdpGLM before loading the saved model object, I receive the above error. If I load hdpGLM and coda, the summary.hdpGLM() method works.
Looking at the code for hdpGLM, I'm noticing that coda is referenced as a namespace with the :: on line 100 of that function (if I open with View(hdpGLM). This loads coda via the namespace when hdpGLM() is called.
Going to dump a lot of code here but running getting session info both before and after a call to hdpGLM confirms this. coda isn't attached before the call, but is attached after.
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.10
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.3.3.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] lme4_1.1-19 Matrix_1.2-14 hdpGLM_1.0.0.0000 forcats_0.3.0 stringr_1.3.1 dplyr_0.7.8 purrr_0.3.0
[8] readr_1.3.1 tidyr_0.8.2 tibble_2.0.1 ggplot2_3.1.0 tidyverse_1.2.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.0 lubridate_1.7.4 lattice_0.20-35 assertthat_0.2.0 digest_0.6.18 R6_2.3.0
[7] cellranger_1.1.0 plyr_1.8.4 backports_1.1.3 acepack_1.4.1 httr_1.4.0 pillar_1.3.1
[13] rlang_0.3.1 lazyeval_0.2.1 readxl_1.2.0 minqa_1.2.4 rstudioapi_0.9.0 data.table_1.11.8
[19] nloptr_1.2.1 rpart_4.1-13 checkmate_1.9.0 splines_3.5.1 foreign_0.8-71 htmlwidgets_1.3
[25] munsell_0.5.0 broom_0.5.1 compiler_3.5.1 modelr_0.1.2 xfun_0.4 pkgconfig_2.0.2
[31] base64enc_0.1-3 htmltools_0.3.6 nnet_7.3-12 tidyselect_0.2.5 gridExtra_2.3 htmlTable_1.13.1
[37] Hmisc_4.1-1 withr_2.1.2 crayon_1.3.4 MASS_7.3-50 grid_3.5.1 nlme_3.1-137
[43] jsonlite_1.6 gtable_0.2.0 magrittr_1.5 scales_1.0.0 cli_1.0.1 stringi_1.2.4
[49] bindrcpp_0.2.2 latticeExtra_0.6-28 xml2_1.2.0 generics_0.0.2 Formula_1.2-3 RColorBrewer_1.1-2
[55] tools_3.5.1 glue_1.3.0 hms_0.4.2 survival_2.42-6 yaml_2.2.0 colorspace_1.3-2
[61] cluster_2.0.7-1 rvest_0.3.2 knitr_1.21 bindr_0.1.1 haven_2.0.0
> model_res <- hdpGLM(data = analysis_df,
+ formula1 = opp_vote_pct ~ mean_dist_ren + turnout + m_opp_vote_pct
+ + dm_opp_vote_pct + dp_opp_vote_pct + kremlin_dist,
+ formula2 = ~ govt_dep + higher_ed + pop_total + pay,
+ context.id = 'region',
+ mcmc = list(burn.in = 100, n.iter = 100),
+ K = 30,
+ family = 'gaussian')
Preparing for estimation ...
Estimation in progress ...
[=======================================================================] 100 %
> sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.10
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.3.3.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] bindrcpp_0.2.2 lme4_1.1-19 Matrix_1.2-14 hdpGLM_1.0.0.0000 forcats_0.3.0 stringr_1.3.1 dplyr_0.7.8
[8] purrr_0.3.0 readr_1.3.1 tidyr_0.8.2 tibble_2.0.1 ggplot2_3.1.0 tidyverse_1.2.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.0 lubridate_1.7.4 lattice_0.20-35 formula.tools_1.7.1 assertthat_0.2.0 digest_0.6.18
[7] R6_2.3.0 cellranger_1.1.0 plyr_1.8.4 backports_1.1.3 acepack_1.4.1 coda_0.19-2
[13] httr_1.4.0 pillar_1.3.1 rlang_0.3.1 lazyeval_0.2.1 readxl_1.2.0 minqa_1.2.4
[19] rstudioapi_0.9.0 data.table_1.11.8 nloptr_1.2.1 rpart_4.1-13 checkmate_1.9.0 splines_3.5.1
[25] foreign_0.8-71 htmlwidgets_1.3 munsell_0.5.0 broom_0.5.1 compiler_3.5.1 modelr_0.1.2
[31] xfun_0.4 pkgconfig_2.0.2 base64enc_0.1-3 htmltools_0.3.6 nnet_7.3-12 tidyselect_0.2.5
[37] gridExtra_2.3 htmlTable_1.13.1 Hmisc_4.1-1 withr_2.1.2 crayon_1.3.4 MASS_7.3-50
[43] grid_3.5.1 nlme_3.1-137 jsonlite_1.6 gtable_0.2.0 magrittr_1.5 scales_1.0.0
[49] cli_1.0.1 stringi_1.2.4 latticeExtra_0.6-28 xml2_1.2.0 generics_0.0.2 Formula_1.2-3
[55] RColorBrewer_1.1-2 tools_3.5.1 glue_1.3.0 hms_0.4.2 survival_2.42-6 yaml_2.2.0
[61] colorspace_1.3-2 cluster_2.0.7-1 operator.tools_1.6.3 rvest_0.3.2 knitr_1.21 bindr_0.1.1
[67] haven_2.0.0 I'm guessing coda contains the function to coerce to dataframe, so this is just a really small dependency issue.
DiogoFerrari
commented
5 years ago done
Model objects (i.e. objects created by a call to
hdpGLM()) that are saved as .rds or .RData no longer seem to work with .hdpGLM methods after being loaded into a new R session.After loading the saved model object, both
plot.hdpGLMandsummary.hdpGLMthrow the following error:This occurs despite the fact that the object is correctly read as class hdpGLM.