Package: nbhdmodel 0.1.0.9000

nbhdmodel: Neighborhood Modeling and Analysis

Functionality for fitting neighborhood models of McCartan, Brown, and Imai <arxiv:2110.14014>. The core methodology is described in the paper and can be implemented with any tool that can fit generalized linear mixed models (GLMMs). However, some of the preprocessing necessary to set up the GLMM can be onerous. In addition to providing a specialized GLMM routine, this package provides several preprocessing functions that, while not completely general, should be useful for others performing these kinds of analyses.

Authors:Cory McCartan [aut, cre], Jacob Brown [aut], Kosuke Imai [aut]

nbhdmodel_0.1.0.9000.tar.gz
nbhdmodel_0.1.0.9000.zip(r-4.5)nbhdmodel_0.1.0.9000.zip(r-4.4)nbhdmodel_0.1.0.9000.zip(r-4.3)
nbhdmodel_0.1.0.9000.tgz(r-4.4-x86_64)nbhdmodel_0.1.0.9000.tgz(r-4.4-arm64)nbhdmodel_0.1.0.9000.tgz(r-4.3-x86_64)nbhdmodel_0.1.0.9000.tgz(r-4.3-arm64)
nbhdmodel_0.1.0.9000.tar.gz(r-4.5-noble)nbhdmodel_0.1.0.9000.tar.gz(r-4.4-noble)
nbhdmodel.pdf |nbhdmodel.html
nbhdmodel/json (API)

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

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

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

cpp

2.48 score 3 stars 9 exports 75 dependencies

Last updated 1 years agofrom:6e7d39e648. Checks:3 OK, 6 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 24 2025
R-4.5-win-x86_64OKJan 24 2025
R-4.5-linux-x86_64OKJan 24 2025
R-4.4-win-x86_64NOTEJan 24 2025
R-4.4-mac-x86_64NOTEJan 24 2025
R-4.4-mac-aarch64NOTEJan 24 2025
R-4.3-win-x86_64NOTEJan 24 2025
R-4.3-mac-x86_64NOTEJan 24 2025
R-4.3-mac-aarch64NOTEJan 24 2025

Exports:binned_residcalc_indiv_framefastAUCfixeflocal_areaneighborhood_modelpost_inclranefsimulate_neighborhood

Dependencies:abindbackportsBHbootcallrcheckmateclassclassIntclicolorspacecpp11DBIdescdistributionaldplyre1071fansifarverfastmatchgenericsggplot2gluegridExtragtableinlineisobandKernSmoothlabelinglatticelifecyclelme4loomagrittrMASSMatrixmatrixStatsmgcvminqamunsellnlmenloptrnumDerivpillarpkgbuildpkgconfigposteriorprocessxproxypsQuickJSRR6rbibutilsRColorBrewerRcppRcppEigenRcppParallelRdpackreformulasrlangrstans2scalessfStanHeadersstringistringrtensorAtibbletidyselectunitsutf8vctrsviridisLitewithrwk

Readme and manuals

Help Manual

Help pageTopics
Binned Residual Plotbinned_resid
Create a model data frame for an individual respondentcalc_indiv_frame
Get Posterior Mean of Effective Block Distanceeff_dist
Calculate AUCfastAUC
Filter block data to a radius of a FIPS codelocal_area
Functions for working with neighborhood fitsas.data.frame.nbhd_fit as.matrix.nbhd_fit coef.nbhd_fit fitted.nbhd_fit fixef.nbhd_fit nbhd_fit ranef.nbhd_fit residuals.nbhd_fit summary.nbhd_fit
Fit the Neighborhood Modelneighborhood_model
Plot coefficient estimatesplot.nbhd_fit
Get Posterior Block Inclusion Probabilitiespost_incl
Simulate a neighborhood for a respondentsimulate_neighborhood