Provides utilities for cleaning survey data, computing weights, and performing descriptive statistical analysis. Methods follow Lohr (2019, ISBN:978-0367272454) "Sampling: Design and Analysis" and Lumley (2010) <doi:10.1002/9780470580066>.

Short and understandable commands that generate tabulated, 
    formatted, and rounded survey estimates. Mostly a wrapper for the 
    'survey' package (Lumley (2004) <doi:10.18637/jss.v009.i08> 
    <https://CRAN.R-project.org/package=survey>) that identifies 
    low-precision estimates using the National Center for Health 
    Statistics (NCHS) presentation standards (Parker et al. (2017) 
    <https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf>,
    Parker et al. (2023) <doi:10.15620/cdc:124368>).

Decision support tool for prioritizing sites for ecological
    surveys based on their potential to improve plans for conserving
    biodiversity (e.g. plans for establishing protected areas). Given a set of
    sites that could potentially be acquired for conservation management,
    it can be used to generate and evaluate plans for surveying additional
    sites. Specifically, plans for ecological surveys can be
    generated using various conventional approaches (e.g. maximizing expected
    species richness, geographic coverage, diversity of sampled environmental
    algorithms. After generating such survey plans, they can be evaluated using
    conditions) and maximizing value of information. Please note that several
    functions depend on the 'Gurobi' optimization software (available from
    <https://www.gurobi.com>). Additionally, the 'JAGS' software (available from
    <https://mcmc-jags.sourceforge.io/>) is required to fit hierarchical
    generalized linear models. For further details, see Hanson et al. (2023) <doi:10.1111/1365-2664.14309>.

The estimation method proposed by Chen and Yi (2021) 
 <doi:10.1111/biom.13331> is extended to the analysis of survival data, 
 accommodating  commonly used survival models while accounting for measurement
 error and network structures among covariates.