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...ormula(assign(paste0("eq",i), value=paste0( "~ x",i," + dummy"))) # define the moment conditions for GMM } # Estimate the model with `sysGmm` using different weighting matrices: identity, "optimal" and manually specified m1 <- sysGmm(g=ES_g, h=ES_h, wmatrix="ident", vcov="MDS" , crossEquConst=3, data=data1) # Error: system is computationally singular m1 <- sysGmm(g=ES_g, h=ES_h, wmatrix="ident", vcov="HAC" , crossEquConst=3, data=data1) # Error: system is computationally singular m1 <- sysGmm(g=ES_g,...

...estricted and unrestricted estimation cec1=NULL # unrestricted cec1=3 # restrict the coefficient on the dummy to be equal across equations # Estimate the model with `sysGmm` using different weighting matrices: identity, "optimal" and manually specified m1a <- sysGmm(g=ES_g, h=ES_h, wmatrix="ident" , weightsMatrix=NULL, vcov=vc1, crossEquConst=cec1, data=data1); summary(m1a) m1b <- sysGmm(g=ES_g, h=ES_h, wmatrix="optimal", weightsMatrix=NULL, vcov=vc1, crossEquConst=cec1, data=data1); summary(m1b) m1c <- sysGmm(g=ES_g, h=ES_h, weightsMatri...

...ion > cec1=NULL # unrestricted > cec1=3 # restrict the coefficient on the dummy to be equal across > equations > > # Estimate the model with `sysGmm` using different weighting matrices: > identity, "optimal" and manually specified > m1a <- sysGmm(g=ES_g, h=ES_h, wmatrix="ident" , weightsMatrix=NULL, > vcov=vc1, crossEquConst=cec1, data=data1); summary(m1a) > m1b <- sysGmm(g=ES_g, h=ES_h, wmatrix="optimal", weightsMatrix=NULL, > vcov=vc1, crossEquConst=cec1, data=data1); summary(m1b) > m1c <- sysGmm(g=ES_g, h=ES_h,...

All, I am new to using R and know some basics. I wish to use kriging in R to do the following: given data Y =f(X1,X2,X3,.....,Xn) --1000+ irregular measured data set. I would like to be able to get a single value y given sinle input set (x1,x2,x3,...xn) A google search on this takes me lierally to the same example on involving analysis with soil sampling and I cannot figure out how to

I have data that looks like this: > df1 group id 1 red A 2 red B 3 red C 4 blue D 5 blue E 6 blue F I want a list of the groups containing vectors with the ids. I am avoiding subset(), as it is only recommended for interactive use. Here's what I have so far: df1 <- data.frame(group=c("red", "red", "red", "blue",