Package: multimput 0.2.14

Thierry Onkelinx

multimput: Using Multiple Imputation to Address Missing Data

Accompanying package for the paper: Working with population totals in the presence of missing data comparing imputation methods in terms of bias and precision. Published in 2017 in the Journal of Ornithology volume 158 page 603–615 (<doi:10.1007/s10336-016-1404-9>).

Authors:Thierry Onkelinx [aut, cre], Koen Devos [aut], Paul Quataert [aut], Research Institute for Nature and Forest [cph, fnd]

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multimput.pdf |multimput.html✨
multimput/json (API)

# Install 'multimput' in R:
install.packages('multimput', repos = c('https://inbo.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/inbo/multimput/issues

Datasets:
  • waterfowl - The observation pattern in the Flemish waterfowl dataset

On CRAN:

imputationimputation-model

3.32 score 1 stars 1 packages 14 scripts 9 exports 48 dependencies

Last updated 2 months agofrom:12d11eff38. Checks:OK: 4 ERROR: 2 WARNING: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-winERRORSep 25 2024
R-4.5-linuxOKNov 03 2024
R-4.4-winOKNov 03 2024
R-4.4-macOKNov 03 2024
R-4.3-winWARNINGSep 25 2024
R-4.3-macERRORNov 05 2024

Exports:aggregate_imputegenerate_datahurdle_imputeimputemissing_at_randommissing_current_countmissing_observedmissing_volunteermodel_impute

Dependencies:assertthatbootclassclassIntclicpp11DBIdigestdplyre1071fansifmeshergenericsglueINLAKernSmoothlatticelifecyclelme4magrittrMASSMatrixMatrixModelsminqamvtnormnlmenloptrpillarpkgconfigproxypurrrR6RcppRcppEigenrlangs2sfspstringistringrtibbletidyrtidyselectunitsutf8vctrswithrwk

Model data with missing observations using multiple imputation

Thierry Onkelinx

Rendered fromimpute.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-10-04
Started: 2022-02-03

Readme and manuals

Help Manual

Help pageTopics
Aggregate an imputed datasetaggregate_impute aggregate_impute,aggregatedImputed-method aggregate_impute,ANY-method aggregate_impute,rawImputed-method
The 'aggregatedImputed' class Holds an aggregated imputation data setaggregatedImputed-class
Generate simulated datagenerate_data
Combine two models into a hurdle modelhurdle_impute
Impute a datasetimpute impute,ANY-method impute,glmerMod-method impute,lm-method impute,maybeInla-method
The 'maybeInla' classmaybeInla-class
Generate missing data at randommissing_at_random
Generate missing data depending on the countsmissing_current_count
Generate missing data based on the observed patterns in the real dataset.missing_observed
Generate missing data mimicking choices made by volunteers.missing_volunteer
Model an imputed datasetmodel_impute model_impute,aggregatedImputed-method model_impute,ANY-method
The 'rawImputed' class Holds a dataset and imputed valuesrawImputed-class
The observation pattern in the Flemish waterfowl datasetwaterfowl