# sv: Semi-variogram computation In sptotal: Predicting Totals and Weighted Sums from Spatial Data

## Description

Compute the empirical semivariogram for a data set with specified x and y spatial coordinates and residuals.

## Usage

 1 sv(data, xcoordcol, ycoordcol, residcol, bins = 15, cutoff = NULL, ...)

## Arguments

 data A data frame or tibble that contains variables for the x coordinates, y coordinates, and residuals. xcoordcol is the name of the column in the data frame with x coordinates or longitudinal coordinates ycoordcol is the name of the column in the data frame with y coordinates or latitudinal coordinates residcol is the name of the column in the data frame with residuals. bins Number of equally spaced semivariogram bins. The default is 15. cutoff The maximum spatial distance to be considered. The default is half of the maximum observed distance in the data frame. ... Additional arguments to be used by stats::dist() for spatial distance calculations.

## Value

A data frame with the average distance in each bin (dist), the semivariance (gamma), and the number of unique pairs in each bin (np)

## Examples

 1 2 3 4 5 6 7 8 9 10 data(exampledataset) ## load a toy data set slmobj <- slmfit(formula = counts ~ pred1 + pred2, data = exampledataset, xcoordcol = 'xcoords', ycoordcol = 'ycoords', areacol = 'areavar') sampleddataset <- na.omit(exampledataset) svexample <- data.frame( xcoords = sampleddataset\$xcoords, ycoords = sampleddataset\$ycoords, resids = residuals(slmobj) ) svdata <- sv(svexample, "xcoords", "ycoords", "resids")

sptotal documentation built on July 6, 2021, 5:07 p.m.