Sill，Nugget，Range

Question

我正在研究Temporal-spatio数据。数据采用STFDF结构。

我正处于应用变异函数的阶段，并尝试从变异函数图中确定看起来像的Nugget，Sill和Range。

这样的事情： 然而，当我绘制我的变异函数时，它显示：

plot(vario, main="Flow")

plot(vario,map=FALSE, main="Spatio-temporal correlation") plot(vario,wireframe=T, main="Spatio-temporal correlation")

如何获得可以定义范围，窗台和金块的情节！我无法从这些图中定义我的参数。 我使用了variogramST函数，并尝试了太变差函数，但两者都无法生成我需要的情节。

vario<-variogramST(Flow~1,data=data,tunit="hours",assumeRegular=F,na.omit=T)

有没有办法定义Range，Nugget和sill ??

####### separable model, least squares fit
separableModel <- vgmST("separable",space=vgm(0.9,"Exp",100,0.1),time=vgm(0.9,"Exp",1000,0.1),sill=40) 
separable_fit <- fit.StVariogram(model=separableModel,object=vario)
plot(vario,separable_fit,all=T,map=F)
attr(separable_fit,"MSE") # calculate the Mean Absolute Error 
### product sum model, least squares fit
ProductSum <- vgmST("productSum",space =vgm(psill= 15000,"Exp",range= 0.07, nugget= 0),time=vgm(psill= 7500,"Exp",range= 0.07, nugget=0),k=0.000649771173341919) 
ProductSum_fit <- fit.StVariogram(model=ProductSum,object=vario)
ProductSum_fit
attr(ProductSum_fit,"MSE") 
plot(vario,ProductSum_fit,all=T,map=F)
plot(vario,ProductSum_fit,all=T)
plot(vario,ProductSum_fit, all=T, wireframe=T)


#### product sum model, manual fit
ProductSum_man <- vgmST("productSum",space=vgm(7500,"Exp",2e5,0,add.to=vgm(10,"Exp",9e3,0)), time=vgm(7500,"Exp",800,9.5,add.to=vgm(0,"Exp",850,0)),k=0.035) 
ProductSum_man_fit <- fit.StVariogram(model=ProductSum_man,object=vario) 
attr(ProductSum_man_fit,"MSE") 
plot(vario,ProductSum_man_fit,all=T,map=F)
plot(vario,ProductSum_man_fit,all=T)