# [R] nls

mzabalazo ngwenya mngwenya at stats.uct.ac.za
Tue Sep 12 13:57:22 CEST 2006

```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)

print (h)  #distance matrix between data
points

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
>

```