Package: gerbil 0.1.9

gerbil: Generalized Efficient Regression-Based Imputation with Latent Processes

Implements a new multiple imputation method that draws imputations from a latent joint multivariate normal model which underpins generally structured data. This model is constructed using a sequence of flexible conditional linear models that enables the resulting procedure to be efficiently implemented on high dimensional datasets in practice. See Robbins (2021) <arxiv:2008.02243>.

Authors:Michael Robbins [aut, cre], Max Griswold [ctb], Pedro Nascimento de Lima [ctb]

gerbil_0.1.9.tar.gz
gerbil_0.1.9.zip(r-4.7-any)gerbil_0.1.9.zip(r-4.6-any)gerbil_0.1.9.zip(r-4.5-any)
gerbil_0.1.9.tgz(r-4.6-any)gerbil_0.1.9.tgz(r-4.5-any)
gerbil_0.1.9.tar.gz(r-4.7-any)gerbil_0.1.9.tar.gz(r-4.6-any)
gerbil_0.1.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
gerbil/json (API)

# Install 'gerbil' in R:

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

Datasets:

ihd - Example data from the India Human Development Survey
ihd_mar - Missing at Random example data from the India Human Development Survey
ihd_mcar - Missing Completely at Random example data from the India Human Development Survey

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 3 scripts 329 downloads 5 exports 59 dependencies

Last updated from:2152129d08. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	140
source / vignettes	OK	195
linux-release	OK	139
macos-release	OK	130
macos-oldrel	OK	119
windows-devel	OK	102
windows-release	OK	93
windows-oldrel	OK	132
wasm-release	OK	108

Exports:cor_gerbil gerbil gof_gerbil imputed write.gerbil

Dependencies:askpass bit bit64 boot cellranger class cli clipr cpp11 crayon curl data.table DescTools e1071 Exact expm forcats fs gld glue haven hms httr jsonlite lattice lifecycle lmom magrittr MASS Matrix mime mvtnorm openssl openxlsx pbapply pillar pkgconfig prettyunits progress proxy R6 Rcpp readr readxl rematch rlang rootSolve rstudioapi stringi sys tibble tidyselect truncnorm tzdb utf8 vctrs vroom withr zip

Gerbil Introduction

Rendered fromgerbil_introduction_vignette.Rnwusingutils::Sweave

Last update: 2021-03-23
Started: 2021-03-23

Help page	Topics
Correlation Analysis for 'gerbil' Objects	cor_gerbil
General Efficient Regression-Based Imputation with Latent processes	gerbil
Goodness-of-fit testing for 'gerbil' objects	gof_gerbil
Example data from the India Human Development Survey	ihd
Missing at Random example data from the India Human Development Survey	ihd_mar
Missing Completely at Random example data from the India Human Development Survey	ihd_mcar
Extracting imputed datasets from gerbil objects	imputed
Plotting for gerbil objects	plot.gerbil
Prints a 'cor_gerbil' object. Printed output includes the average difference of correlations, as well as summaries of the test statistics based on Fisher's z and their p-values.	print.cor_gerbil
Prints a 'gerbil' object. Printed output includes a variable-by-variable summary of variable types and missingness rates. The implemented predictor matrix is also provided.	print.gerbil
Prints a 'gof_gerbil' object. Printed output pertains to the goodness-of-fit tests that are applied in order to compare the distribution between observed and imputed cases for relevant variables or variable pairs.	print.gof_gerbil
Summarises a 'gerbil' object. Printed output includes a variable-by-variable summary of variable types and missingness rates. The implemented predictor matrix is also provided.	summary.cor_gerbil
Summarises a 'gerbil' object. Printed output includes a variable-by-variable summary of variable types and missingness rates. The implemented predictor matrix is also provided.	summary.gerbil
Summarises a 'gerbil' object. Printed output pertains to the goodness-of-fit tests that are applied in order to compare the distribution between observed and imputed cases for relevant variables or variable pairs.	summary.gof_gerbil
Write imputed datasets from gerbil objects to a file or files	write.gerbil

Package: gerbil 0.1.9

gerbil: Generalized Efficient Regression-Based Imputation with Latent Processes

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)