Local Log-linear Models for Capture-Recapture

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Documentation for package ‘lllcrc’ version 1.2

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lllcrc-package Local Log-linear Models for Capture-Recapture
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
init.pop Set up a fake population
initialize.u.vec Initialize log-linear parameters
llcrc.flat.boots Bootstrapping LLMs
lllcrc Local log-linear models (LLLMs) for capture-recapture (CRC)
lllcrc.boots Bootstrap for LLLMs
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.lllcrc Plot LLLMs
plot.llsim Plot the output of 'llm.sim'
plot.vgam.crc Plot LLLMs
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.lllcrc Summary of LLLM or VGAM CRC analysis
summary.vgam.crc 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