>#6、地理加权回归操作(高斯函数)>col.gauss <- gwr(CRIME ~ INC + HOVAL, data=columbus,+coords=cbind(columbus$X, columbus$Y),+bandwidth=col.bw, hatmatrix=TRUE)>col.gaussCall:gwr(formula=CRIME ~ INC + HOVAL, data = columbus, coords = cbind(columbus$X,columbus$Y),bandwidth = col.bw,...
在该包中,运行线性地理加权回归的函数是gwr()。语法结构如下: gwr(formula, data = list(), coords, bandwidth, gweight = gwr.Gauss, adapt = NULL, hatmatrix = FALSE, fit.points, longlat = NULL, se.fit = FALSE, weights, cl = NULL, predictions = FALSE, fittedGWRobject = NULL, se.fit....
family = binomial(), bandwidth = bw) ## 查看模型统计量 model ## Call: ## ggwr(formula = form, data = londonhp, bandwidth = bw, family = binomial()) ## Kernel function: gwr.Gauss ## Fixed bandwidth: 57238.62 ## Summary of GWR coefficient estimates at data points: ## Min. 1st Q...
带宽(bandwidth)确定了局部的范围,该包的gwr.sel()函数提供了两种确定带宽的方法:交叉验证法和AIC信息准则法。语法结构如下: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 gwr.sel(formula, data = list(), coords, adapt = FALSE, gweight = gwr.Gauss, method = "cv", verbose = TRUE, longlat...
[R-sig-Geo] How to get each bandwidth values on observation points using adaptive kernel in spgwr ? B Rowlingson 被引量: 0发表: 0年 [R-sig-Geo] About adaptive spatial kernel for spgwr H Ono 被引量: 0发表: 0年 [R-sig-Geo] About adaptive spatial kernel for spgwr D Yu 被引量: ...
Package SPGWR:将GWR模型参数应用于更精细的空间比例为了使用spgwr包将GWR的模型参数应用于更精细的空间比例:1.以粗略比例计算GWR 1.使用参数fit.points、predictions和fittedGWRobject再次应用步骤1。代码:
{ if(!inherits(x, "gwr")) stop("not a gwr object") cat("Call:\n") print(x$this.call) cat("Kernel function:", x$gweight, "\n") n <- length(x$lm$residuals) if (is.null(x$adapt)) cat("Fixed bandwidth:", x$bandwidth, "\n") else cat("Adaptive quantile: ", x$adapt,...
>#6、地理加权回归操作(高斯函数)>col.gauss <- gwr(CRIME ~ INC + HOVAL, data=columbus,+coords=cbind(columbus$X, columbus$Y),+bandwidth=col.bw, hatmatrix=TRUE)>col.gaussCall:gwr(formula=CRIME ~ INC + HOVAL, data = columbus, coords = cbind(columbus$X,columbus$Y),bandwidth = col.bw...