spsurvey5.5.1 package

Spatial Sampling Design and Analysis

Internal Function: Variance-Covariance Matrix Based on Local Mean Esti...

Internal Function: Local Mean Variance Estimator

Internal Function: Local Mean Variance Neighbors and Weights

Summary characteristics of a panel revisit design

Plot sampling frames, design sites, and analysis data.

Plot a cumulative distribution function (CDF)

Power calculation for multiple panel designs

Plot power curves for panel designs

Relative risk analysis

Adjust survey design weights by categories

Adjust survey design weights for non-response by categories

Compute the average shifted histogram (ASH) for one-dimensional weight...

Attributable risk analysis

Categorical variable analysis

Plot a cumulative distribution function (CDF)

Change analysis

Continuous variable analysis

Create a PDF file containing cumulative distribution functions (CDF) p...

Cumulative distribution function (CDF) inference for a probability sur...

Create a covariance matrix for a panel design

Risk difference analysis

Print errors from analysis functions

Select a generalized random tessellation stratified (GRTS) sample

Select an independent random sample (IRS)

Create a balanced incomplete block panel revisit design

Create a panel revisit design

Create a revisit design with random assignment to panels and time peri...

Calculate spatial balance metrics

`sp_frame`

objects

Plot sampling frames, design sites, and analysis data.

Combine rows from GRTS or IRS samples.

Summarize sampling frames, design sites, and analysis data.

spsurvey: Spatial Sampling Design and Analysis

Print grts() and irs() errors.

Summarize sampling frames, design sites, and analysis data.

Trend analysis

Print grts(), irs()), and analysis function warnings

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>.

Maintainer: Michael Dumelle License: GPL (>= 3) Last published: 2024-01-09

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