# Calc_Kmeans: Calculates locations for knots used in piecewise constant... In James-Thorson/spatial_condition_factor: Package for estimating spatial and spatiotemporal variation in individual condition.

## Usage

 1 Calc_Kmeans(n_x, Kmeans_Config, Data_Geostat, Data_Extrap)

## Arguments

 n_x Kmeans_Config Data_Geostat Data_Extrap

## Examples

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 ##---- Should be DIRECTLY executable !! ---- ##-- ==> Define data, use random, ##-- or do help(data=index) for the standard data sets. ## The function is currently defined as function (n_x, Kmeans_Config, Data_Geostat, Data_Extrap) { old.options <- options() options(warn = -1) on.exit(options(old.options)) if (paste0("Kmeans-", n_x, ".RData") %in% list.files(getwd())) { load(file = paste(DateFile, "Kmeans.RData", sep = "")) } else { Kmeans = list(tot.withinss = Inf) for (i in 1:Kmeans_Config[["nstart"]]) { if (Kmeans_Config[["Locs"]] == "Samples") { Tmp = kmeans(x = Data_Geostat[, c("E_km", "N_km")], centers = n_x, iter.max = Kmeans_Config[["iter.max"]], nstart = 1, trace = 0) } if (Kmeans_Config[["Locs"]] == "Domain") { Tmp = kmeans(x = Data_Extrap[, c("E_km", "N_km")], centers = n_x, iter.max = Kmeans_Config[["iter.max"]], nstart = 1, trace = 0) } print(paste0("Num=", i, " Current_Best=", round(Kmeans\$tot.withinss, 1), " New=", round(Tmp\$tot.withinss, 1))) if (Tmp\$tot.withinss < Kmeans\$tot.withinss) { Kmeans = Tmp } } } return(Kmeans) }

James-Thorson/spatial_condition_factor documentation built on May 7, 2019, 10:20 a.m.