返回在R中的地理加权回归的全局R2。

Question

我使用R库在spgwr中运行了一个地理加权回归(GWR)，现在我想返回准全局R2 (模型的拟合)。我已经使用summary(gwr_model)深入研究了结果，但是我还没有找到提取这个值的方法。有什么想法吗？

可复制示例

library(spgwr)

# load data
  data(columbus)

# calculate Optimal kernel bandwidth 
  col.bw <- gwr.sel(crime ~ income + housing, data=columbus, coords=cbind(columbus$x, columbus$y))
# run GWR
  gwr_model <- gwr(crime ~ income + housing, data=columbus,
                   coords=cbind(columbus$x, columbus$y), bandwidth=col.bw, hatmatrix=TRUE)

# get global coefficients
  gwr_model$lm$coefficients


# print results. It shows the Quasi-global R2: 0.9071
  gwr_model

  #> Call:
  #>   gwr(formula = crime ~ income + housing, data = columbus, coords = cbind(columbus$x, 
  #>                                                                           columbus$y), bandwidth = col.bw, hatmatrix = TRUE)
  #> Kernel function: gwr.Gauss 
  #> Fixed bandwidth: 2.275 
  #> Summary of GWR coefficient estimates at data points:
  #>   Min. 1st Qu.  Median 3rd Qu.    Max. Global
  #> X.Intercept. 23.2332 54.1252 63.9024 68.7564 80.9009  68.62
  #> income       -3.1307 -1.9129 -0.9844 -0.3686  1.2911  -1.60
  #> housing      -1.0528 -0.3767 -0.0974  0.0301  0.7946  -0.27
  #> Number of data points: 49 
  #> Effective number of parameters (residual: 2traceS - traceS'S): 29.62 
  #> Effective degrees of freedom (residual: 2traceS - traceS'S): 19.38 
  #> Sigma (residual: 2traceS - traceS'S): 8.027 
  #> Effective number of parameters (model: traceS): 23.93 
  #> Effective degrees of freedom (model: traceS): 25.07 
  #> Sigma (model: traceS): 7.058 
  #> Sigma (ML): 5.049 
  #> AICc (GWR p. 61, eq 2.33; p. 96, eq. 4.21): 403.6 
  #> AIC (GWR p. 96, eq. 4.22): 321.7 
  #> Residual sum of squares: 1249 
  #> Quasi-global R2: 0.9071 

Answer 1

如果你想要的是得到“准全局R2"，源代码表明至少可以计算它。

qGlobalR2 <- (1 - (gwr_model$results$rss/gwr_model$gTSS))