findres: Choose spatial resolution for analysis In ppmlasso: Point Process Models with LASSO Penalties

Description

This function produces a plot to choose the optimal spatial resolution for analysis. A point process model is calculated for each nominated spatial resolution and the log-likelihood of all fitted models are plotted against the spatial resolutions.

Usage

 1 findres(scales, lambda = 0, coord = c("X", "Y"), sp.xy, env.grid, formula, ...)

Arguments

 scales A vector of spatial resolutions for which to produce the plot. lambda The LASSO penalty for each fitted spatial resolution. This should be a single value such that only one point process model is computed for each spatial resolution. coord A vector containing the names of the longitude and latitude coordinates, used by env.var. sp.xy A matrix of species locations containing at least one column representing longitude and one column representing latitude, as in ppmlasso. env.grid The geo-referenced matrix of environmental grids, as in ppmlasso. formula The formula of the fitted model, as in ppmlasso. ... Further arguments passed to ppmlasso.

Value

A plot of log-likelihood versus spatial resolution.

Ian W. Renner

Examples

 1 2 3 4 5 6 data(BlueMountains) sub.env = BlueMountains\$env[BlueMountains\$env\$Y > 6270 & BlueMountains\$env\$X > 300,] sub.euc = BlueMountains\$eucalypt[BlueMountains\$eucalypt\$Y > 6270 & BlueMountains\$eucalypt\$X > 300,] scales = c(0.5, 1, 2, 4, 8, 16) ppm.form = ~ poly(FC, TMP_MIN, TMP_MAX, RAIN_ANN, degree=2) findres(scales, formula = ppm.form, sp.xy = sub.euc, env.grid = sub.env)

ppmlasso documentation built on May 2, 2019, 8:20 a.m.