AICc.vgam               Compute the AICc for a VGAM model
age.sex.zip             Simulate CRC data with age, sex, and zip code
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-package          Local Log-linear Models for Capture-Recapture
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'
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
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
