[R] nls

[Spencer Graves]

      I used "debug" to walk through your example line by line,  I found 
that the error message was misleading.  By making 
as.vector(semivariance) and as.vector(h)  columns of a data.frame, I got 
it to work.  My revised code appears below. 

      Thanks for providing a self-contained and relatively simple 
example.  Without it, I could have done little more that suggest 
'traceback' (which provided zero information when I tried it) and 'debug'. 

      Hope this helps. 
      Spencer Graves

fit.gaus<-function(coordinates,values,guess.c0,guess.c1,guess.a)
{
         long<-rep(coordinates[,1],each=length(coordinates[,1]))
       
lag.long<-t(matrix(long,nrow=length(coordinates[,1]),byrow=TRUE))
         dif.long <-(lag.long-t(lag.long))^2
         lat <-rep(coordinates[,2],each=length(coordinates[,2]))
         lag.lat<-t(matrix(lat,nrow=length(coordinates[,2]),byrow=TRUE))
         dif.lat <-(lag.lat-t(lag.lat))^2
         h <-sqrt(dif.long+dif.lat)
        
                                       
         if( length(values[1,])>1)
               {
                     y.m <-apply(values,1,sum,na.rm=TRUE)
                     y.m <-as.matrix(y.m)
                     y.mod <-(1/length(values[1,]))*(y.m)
            }
         else
               {
                      y.mod <-as.matrix(values)
            }

        semi <-rep(y.mod,each=length(y.mod))
        mat1<-t(matrix(semi,nrow=length(y.mod),byrow=TRUE))
        mat2<-t(mat1)
        semivariance <-(1/2)*(mat1-mat2)^2

#        model <-semivariance ~c0+c1*(1-exp(-(h^2)/a^2))
         DF <- data.frame(smvar=as.vector(semivariance),
                          h.=as.vector(h) )
         mdl <- smvar~c0+c1*(1-exp(-(h.^2)/a^2))
        
#        parameters <-nls(model,start =
#list(c0=guess.c0,c1=guess.c1,a=guess.a),trace=TRUE)
        parameters <-nls(mdl,start =
list(c0=guess.c0,c1=guess.c1,a=guess.a),trace=TRUE,
                         data=DF )
        results <-summary(parameters)
                      print(results)
}

################################
mzabalazo ngwenya wrote:
> Hello everyone !
>
> I am trying to write a short program to estimate  semivariogram
> parameters. But I keep running into a problem when using the nls
> function.
>
> Could you please shed some light. I have put a sample of one of the
> codes and ran a short example so you see what I mean.
>
> -----------------
>
>
>
> fit.gaus<-function(coordinates,values,guess.c0,guess.c1,guess.a)
> {
>          long<-rep(coordinates[,1],each=length(coordinates[,1]))
>         
> lag.long<-t(matrix(long,nrow=length(coordinates[,1]),byrow=TRUE))
>          dif.long <-(lag.long-t(lag.long))^2
>          lat <-rep(coordinates[,2],each=length(coordinates[,2]))
>          lag.lat<-t(matrix(lat,nrow=length(coordinates[,2]),byrow=TRUE))
>          dif.lat <-(lag.lat-t(lag.lat))^2
>          h <-sqrt(dif.long+dif.lat) 
>          
>                                         
>          if( length(values[1,])>1)
>                {
>                      y.m <-apply(values,1,sum,na.rm=TRUE)
>                      y.m <-as.matrix(y.m)
>                      y.mod <-(1/length(values[1,]))*(y.m)
>             }
>          else
>                {
>                       y.mod <-as.matrix(values)
>             }
>
>         semi <-rep(y.mod,each=length(y.mod))
>         mat1<-t(matrix(semi,nrow=length(y.mod),byrow=TRUE))
>         mat2<-t(mat1)
>         semivariance <-(1/2)*(mat1-mat2)^2
>
>         model <-semivariance ~c0+c1*(1-exp(-(h^2)/a^2)) 
>         parameters <-nls(model,start =
> list(c0=guess.c0,c1=guess.c1,a=guess.a),trace=TRUE)
>         results <-summary(parameters)
>                       print(results)
> } 
> --------------------------
>
>   
>>  don <-matrix(c(2,3,9,6,5,2,7,9,5,3),5,2)
>> don
>>     
>      [,1] [,2]
> [1,]    2    2
> [2,]    3    7
> [3,]    9    9
> [4,]    6    5
> [5,]    5    3
>   
>>  data <-matrix(c(3,4,2,4,6))
>> data
>>     
>      [,1]
> [1,]    3
> [2,]    4
> [3,]    2
> [4,]    4
> [5,]    6
>   
>> fit.gaus(don,data,2,3,5)
>>     
>          [,1]     [,2]     [,3]     [,4]     [,5]
> [1,] 0.000000 5.099020 9.899495 5.000000 3.162278
> [2,] 5.099020 0.000000 6.324555 3.605551 4.472136
> [3,] 9.899495 6.324555 0.000000 5.000000 7.211103
> [4,] 5.000000 3.605551 5.000000 0.000000 2.236068
> [5,] 3.162278 4.472136 7.211103 2.236068 0.000000
> 178.9113 :  2 3 5 
> Error in qr.qty(QR, resid) : 'qr' and 'y' must have the same number of
> rows
>   
>
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