NSUM: Network Scale Up Method
Version 1.0

A Bayesian framework for population group size estimation using the Network Scale Up Method (NSUM). Size estimates are based on a random degree model and include options to adjust for barrier and transmission effects.

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AuthorRachael Maltiel and Aaron J. Baraff
Date of publication2015-03-03 21:37:49
MaintainerAaron J. Baraff <ajbaraff@uw.edu>
LicenseGPL-2 | GPL-3
Version1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("NSUM")

Man pages

Curitiba: Curitiba Dataset
killworth: Calculate Killworth Estimates
killworth.start: Killworth Starting Values for MCMC
McCarty: McCarty Dataset
nsum.mcmc: Run MCMC for NSUM Parameters
NSUM-package: NSUM: Network Scale Up Method
nsum.simulate: Simulate NSUM Data

Functions

Curitiba Man page
McCarty Man page
NSUM Man page
NSUM-package Man page
killworth Man page Source code
killworth.start Man page Source code
loglik.NK.rd Source code
loglik.di.bar Source code
loglik.di.comb Source code
loglik.di.rd Source code
loglik.di.trans Source code
loglik.mK.bar Source code
loglik.mK.comb Source code
loglik.qik.comb Source code
loglik.rhok.bar Source code
loglik.rhok.comb Source code
loglik.tauK.comb Source code
loglik.wK.trans Source code
loglik.zK.trans Source code
mcmc.bar Source code
mcmc.comb Source code
mcmc.rd Source code
mcmc.trans Source code
nsum.mcmc Man page Source code
nsum.simulate Man page Source code
simulate.bar Source code
simulate.comb Source code
simulate.rd Source code
simulate.trans Source code

Files

NAMESPACE
data
data/McCarty.RData
data/Curitiba.RData
R
R/MCMC_barrier_transmission_combined.R
R/MCMC_barrier_effect.R
R/MCMC_master.R
R/MCMC_transmission_bias.R
R/MCMC_random_degree.R
R/killworth.R
MD5
DESCRIPTION
man
man/nsum.mcmc.Rd
man/NSUM-package.Rd
man/killworth.Rd
man/Curitiba.Rd
man/McCarty.Rd
man/killworth.start.Rd
man/nsum.simulate.Rd
NSUM documentation built on May 19, 2017, 10:34 p.m.