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>).

Provides 'dplyr' and 'tidyr' verbs, survey-aware recoding
    helpers, and row-wise statistics for survey design objects created with
    the 'surveycore' package. filter() uses domain estimation to preserve
    variance estimation validity; other verbs preserve design variables and
    metadata automatically. Also supports survey_collection objects for
    applying the same operation across a list of surveys.

Makes it easy to install and load a collection of packages for survey analysis
    that build upon the foundational 'survey' package of Lumley (2004) <doi:10.18637/jss.v009.i08>.
    Schneider (2025) <https://isi-iass.org/home/wp-content/uploads/Survey_Statistician_2025_January_N91_06.pdf>
    describes the three core packages in this collection.

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>.