Perform the Kriging variance.
[S,V]=NL_F_KrigingVar(L,Gv)
vector.
G vector.
Standard error.
Variance.
NL_F_KrigingVar performs the Kriging variance V (). If errors are normally distributed, we have: Kriging Predictor +-1.96*sqrt(kriging variance). The prediction interval is [K-1.96*s : K+1.96*s].
x=[1,3,1,4,5]; y=[5,4,3,5,1]; z=[100,105,105,100,115]; n=length(x); [k,l,d,s]=NL_F_SemiVariogram(x,y,z);//semi-variogram ni=100;//number of inter-slope between 0 and max slope [os,isl,di]=NL_F_SemiVariogramFit(s,d,ni);//fit [g]=NL_F_GammaMatrix(os,k,l,d,n);//Gamma Matrix xi=1; yi=4; [dv,gv]=NL_F_ForecastXY(g,os,x,y,xi,yi);//semi-variogram in (xi,yi) [lambda]=NL_F_ForecastLambda(g,gv);//computation of Lambda [P,K]=NL_F_KrigingPred(lambda,z);//Kriging predictor [sd,v]=NL_F_KrigingVar(lambda,gv);//application of NL_F_KrigingVar | ![]() | ![]() |