lllcrc: Local Log-linear Models for Capture-Recapture

Applies local log-linear capture-recapture models (LLLMs) for closed populations, as described in the doctoral thesis of Zachary Kurtz. The method is relevant when there are 3-5 capture occasions, with auxiliary covariates available for all capture occasions. As part of estimating the number of missing population units, the method estimates the "rate of missingness" as it varies over the covariate space. In addition, user-friendly functions are provided to recreate (approximately) the method of Zwane and van der Heijden (2004), which applied the VGAM package in a way that is closely related to LLLMs.

Install the latest version of this package by entering the following in R:
install.packages("lllcrc")
AuthorZach Kurtz
Date of publication2014-10-06 00:53:14
MaintainerZach Kurtz <zkurtz@gmail.com>
LicenseGPL-2
Version1.2

View on CRAN

Man pages

age.sex.zip: Simulate CRC data with age, sex, and zip code

AICc.vgam: Compute the AICc for a VGAM model

apply.ic.fit: Select an LLLM at each point

apply.local.ml: Fit LLLMs

as.num: Conversion to numeric

captures: Simulating captures

construct.vgam: Make a VGAM model

extract.CI: Use bootstrap output to get CI

flat.IC: Select an LLM

flat.log.linear: Fit an LLM

formatdata: Format the CRC data

french.1: A fake dataset, french.1

get.IC: Compute an information criterion

ic.all: Compute an IC for several LLMs

ic.fit: Select and fit an LLM

ic.wghts: Information criterion model weights

initialize.u.vec: Initialize log-linear parameters

init.pop: Set up a fake population

llcrc.flat.boots: Bootstrapping LLMs

lllcrc: Local log-linear models (LLLMs) for capture-recapture (CRC)

lllcrc.boots: Bootstrap for LLLMs

lllcrc-package: Local Log-linear Models for Capture-Recapture

llm.sim: Simulate basic log-linear CRC experiments

local.ml: Maximum likelihood estimation for fixed LLLMs

make.design.matrix: Construct standard LLM design matrix.

make.hierarchical.term.sets: Generate a universe of hierarchical models.

make.patterns.template: Template for capture-pattern counts

micro.post.stratify: Collapse CRC data through micro post-stratification

odd.evens: Determine the even-ness of capture patterns

patterns: Collapse capture events into capture patterns (strings)

patterns.possible: Generate all observable capture patterns

pirls: Maximum likelihood for log-linear coefficients

plot: Plot LLLMs

plot.llsim: Plot the output of 'llm.sim'

pop.to.counts: Put CRC data into LLM vector

poptop: Simulate a CRC experiment

rates.by.category: Display estimated rates of missingness by category

resample.captures: Tool for bootstrapping

saturated.local: Use odd-even formula to fit saturated LLM

smooth.patterns: Local averaging for LLLMs

stackydens: Stack local capture pattern frequencies for plotting

string.to.array: Put LLM vector into a LLM design matrix

summarize.by.factors: Summarize LLLM by factor

summary: Summary of LLLM or VGAM CRC analysis

vgam.crc: Build a VGAM CRC model

vgam.crc.boots: Bootstrapping for a VGAM CRC model

y.string.to.y.glm: Capture patterns to design matrix

zglm: Maximum likelihood for log-linear coefficients

Functions

age.sex.zip Man page
AICc.vgam Man page
apply.ic.fit Man page
apply.local.ml Man page
as.num Man page
captures Man page
construct.vgam Man page
extract.CI Man page
flat.IC Man page
flat.log.linear Man page
formatdata Man page
french.1 Man page
get.IC Man page
ic.all Man page
ic.fit Man page
ic.wghts Man page
initialize.u.vec Man page
init.pop Man page
llcrc.flat.boots Man page
lllcrc Man page
lllcrc.boots Man page
lllcrc-package Man page
llm.sim Man page
local.ml Man page
make.design.matrix Man page
make.hierarchical.term.sets Man page
make.patterns.template Man page
micro.post.stratify Man page
odd.evens Man page
patterns Man page
patterns.possible Man page
pirls Man page
plot.lllcrc Man page
plot.llsim Man page
plot.vgam.crc Man page
pop.to.counts Man page
poptop Man page
rates.by.category Man page
resample.captures Man page
saturated.local Man page
smooth.patterns Man page
stackydens Man page
string.to.array Man page
summarize.by.factors Man page
summary.lllcrc Man page
summary.vgam.crc Man page
vgam.crc Man page
vgam.crc.boots Man page
y.string.to.y.glm Man page
zglm Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.