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Last data update: 2014.03.03

R: Bayesian Nonparametric Latent Class Capture-Recapture

lcmCR

R Documentation

Bayesian Nonparametric Latent Class Capture-Recapture

Description

Create and initialize an object of class lcm_CR_Basic.

Usage

lcmCR(captures, tabular = FALSE, in_list_label = "1", not_in_list_label = "0", 
  K = 5, a_alpha = 0.25, b_alpha = 0.25, buffer_size = 10000, thinning = 10, 
  seed = "auto", verbose = TRUE)

Arguments

`captures`	input dataset. A data frame with the multiple-recapture data. See 'Details' for input formats.
`tabular`	a logical value indicating whether or not the data is tabulated. See 'Details'.
`in_list_label`	factor label that indicates that individual is in list (e.g. 'Yes')
`not_in_list_label`	factor label that indicates that individual is in not list (e.g. 'No')
`K`	maximum number of latent classes. Indicates the truncation level of the stick-breaking process.
`a_alpha`	shape parameter of the prior distribution of concentration parameter of the stick-breaking process.
`b_alpha`	inverse scale parameter of the prior distribution of concentration parameter of the stick-breaking process.
`buffer_size`	size of the tracing buffer.
`thinning`	thinning interval for the tracing buffer
`seed`	integer seed of the internal RNG.
`verbose`	Generate progress messages?

Details

Input data must be provided as a data frame. The first J columns are two-level factors representing the multiple-recapture lists. Arguments in_list_label and not_in_list_label indicate the labels that represent inclusion and exclusion from the lists. This function supports two input formats:

When tabular=FALSE each row represents a single individual's capture history. The number of rows must match the size of the observed population. Rows indicating no capture in all list simultaneously are illegal.
When tabular=TRUE each row represents a particular capture pattern. This format requires an additional numeric column at the right indicating the count corresponding to such pattern.

Value

An object of class lcm_CR_Basic initialized, after running burnin iterations.

Author(s)

Daniel Manrique-Vallier

Examples

require('LCMCR')
data(kosovo_aggregate)
sampler <- lcmCR(captures = kosovo_aggregate, tabular = FALSE, in_list_label = '1',
  not_in_list_label = '0', K = 10, a_alpha = 0.25, b_alpha = 0.25,
  seed = 'auto', buffer_size = 10000, thinning = 100)
sampler
N <- lcmCR_PostSampl(sampler, burnin = 10000, samples = 1000, thinning = 100)
quantile(N, c(0.025, 0.5, 0.975))

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(LCMCR)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/LCMCR/lcmCR.Rd_%03d_medium.png", width=480, height=480)
> ### Name: lcmCR
> ### Title: Bayesian Nonparametric Latent Class Capture-Recapture
> ### Aliases: lcmCR
> ### Keywords: capture-recapture
> 
> ### ** Examples
> 
> require('LCMCR')
> data(kosovo_aggregate)
> sampler <- lcmCR(captures = kosovo_aggregate, tabular = FALSE, in_list_label = '1',
+   not_in_list_label = '0', K = 10, a_alpha = 0.25, b_alpha = 0.25,
+   seed = 'auto', buffer_size = 10000, thinning = 100)
WARMING UP...
> sampler
	Initialized = TRUE 
	Current iteration = 0 
Tracer:
	Activated = FALSE 
	Capacity = 10000 samples.
	Used  = 0 (0%)
	Thining = 100 
	Currently Tracing:  
> N <- lcmCR_PostSampl(sampler, burnin = 10000, samples = 1000, thinning = 100)
> quantile(N, c(0.025, 0.5, 0.975))
     2.5%       50%     97.5% 
 9214.925 10388.500 13074.575 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>