spsurvey: Spatial Sampling Design and Analysis

A design-based approach to statistical inference, with a focus on spatial data. Spatially balanced samples are selected using the Generalized Random Tessellation Stratified (GRTS) algorithm. The GRTS algorithm can be applied to finite resources (point geometries) and infinite resources (linear / linestring and areal / polygon geometries) and flexibly accommodates a diverse set of sampling design features, including stratification, unequal inclusion probabilities, proportional (to size) inclusion probabilities, legacy (historical) sites, a minimum distance between sites, and two options for replacement sites (reverse hierarchical order and nearest neighbor). Data are analyzed using a wide range of analysis functions that perform categorical variable analysis, continuous variable analysis, attributable risk analysis, risk difference analysis, relative risk analysis, change analysis, and trend analysis. spsurvey can also be used to summarize objects, visualize objects, select samples that are not spatially balanced, select panel samples, measure the amount of spatial balance in a sample, adjust design weights, and more. For additional details, see Dumelle et al. (2023) <doi:10.18637/jss.v105.i03>.

Package details

AuthorMichael Dumelle [aut, cre] (<https://orcid.org/0000-0002-3393-5529>), Tom Kincaid [aut], Tony Olsen [aut], Marc Weber [aut], Don Stevens [ctb], Denis White [ctb]
MaintainerMichael Dumelle <Dumelle.Michael@epa.gov>
LicenseGPL (>= 3)
Version5.5.0
URL https://usepa.github.io/spsurvey/ https://github.com/USEPA/spsurvey
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("spsurvey")

Try the spsurvey package in your browser

Any scripts or data that you put into this service are public.

spsurvey documentation built on May 31, 2023, 6:25 p.m.