Package: adjustr 0.1.2

adjustr: Stan Model Adjustments and Sensitivity Analyses using Importance Sampling

Functions to help assess the sensitivity of a Bayesian model (fitted using the rstan pakcage) to the specification of its likelihood and priors. Users provide a series of alternate sampling specifications, and the package uses Pareto-smoothed importance sampling to estimate posterior quantities of interest under each specification.

Authors:Cory McCartan [aut, cre]

adjustr_0.1.2.tar.gz
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adjustr.pdf |adjustr.html✨
adjustr/json (API)
NEWS

# Install 'adjustr' in R:

install.packages('adjustr', repos = c('https://corymccartan.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/corymccartan/adjustr/issues

On CRAN:

5 exports 9 stars 1.00 score 57 dependencies 5 scripts

Last updated 4 years agofrom:2347cb57a9 (on v0.1.2). Checks:OK: 1 ERROR: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Aug 20 2024
R-4.5-win	ERROR	Aug 20 2024
R-4.5-linux	ERROR	Aug 20 2024
R-4.4-win	ERROR	Aug 20 2024
R-4.4-mac	ERROR	Aug 20 2024
R-4.3-win	ERROR	Aug 20 2024
R-4.3-mac	ERROR	Aug 20 2024

Exports:adjust_weights extract_samp_stmts get_resampling_idxs make_spec spec_plot

Dependencies:abind backports BH callr checkmate cli colorspace desc distributional dplyr fansi farver generics ggplot2 glue gridExtra gtable inline isoband labeling lattice lifecycle loo magrittr MASS Matrix matrixStats mgcv munsell nlme numDeriv pillar pkgbuild pkgconfig posterior processx ps purrr QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel rlang rstan scales StanHeaders stringi stringr tensorA tibble tidyselect utf8 vctrs viridisLite withr

Sensitivity Analysis of a Simple Hierarchical Model

Rendered fromeight-schools.Rmdusingknitr::rmarkdownon Aug 20 2024.

Last update: 2021-02-09
Started: 2020-04-24

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Compute Pareto-smoothed Importance Weights for Alternative Model Specifications	adjust_weights
adjustr: Stan Model Adjustments and Sensitivity Analyses using Importance Sampling	adjustr
Convert an 'adjustr_spec' Object Into a Data Frame	as.data.frame.adjustr_spec
'dplyr' Methods for 'adjustr_spec' Objects	arrange.adjustr_spec dplyr.adjustr_spec filter.adjustr_spec rename.adjustr_spec select.adjustr_spec slice.adjustr_spec
Extract Model Sampling Statements From a Stan Model.	extract_samp_stmts
Get Importance Resampling Indices From Weights	get_resampling_idxs
Set Up Model Adjustment Specifications	make_spec
Extract Weights From an 'adjustr_weighted' Object	pull.adjustr_weighted
Plot Posterior Quantities of Interest Under Alternative Model Specifications	spec_plot
Summarize Posterior Distributions Under Alternative Model Specifications	summarise.adjustr_weighted summarize.adjustr_weighted