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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 |