I tried a program on S-plus, and it worked. Also I tried the same program on R but not worked. Here is the programme. I put it in a function form. The model and assumption are at the bottom.
where counts<-c(22,2,2,0,5,7,14,0,0,2,36,0,0,1,17,10) which is name.data, i is row size and j is the column size.
symmetry
function(i, j, name.data)
{
row <- (c(1:i))
col <- (c(1:j))
name.data <- expand.grid(A = row, B = col)
name.data$counts <- c(counts)
name.data$symm <- paste(pmin(as.numeric(name.data$A), as.numeric(name.data$B)), pmax(as.numeric(name.data$A), as.numeric(name.data$B)), sep = ",")
symmetry <- glm(counts ~ symm, family = poisson(link = log), data = name.data)
}
> summary(symmetry(4,4,counts))
Call: glm(formula = counts ~ symm, family = poisson(link = log), data = name.data)
Deviance Residuals:
Min 1Q Median 3Q Max
-4.123106 -0.9044956 -3.846197e-008 0.6543513 2.562617
Coefficients:
Value Std. Error t value
(Intercept) 0.7912419 2.1128915 0.3744830
symm1 -0.9191397 0.2169745 -4.2361653
symm2 -0.7239676 0.2465491 -2.9364038
symm3 -2.3094242 5.2703608 -0.4381909
symm4 0.5614798 1.0575027 0.5309488
symm5 0.3965751 0.7045443 0.5628817
symm6 -0.1128162 0.5223163 -0.2159920
symm7 0.4499711 0.3777980 1.1910362
symm8 0.1895939 0.2946399 0.6434767
symm9 0.1679270 0.2368599 0.7089720(Dispersion Parameter for Poisson family taken to be 1 )
Null Deviance: 190.398 on 15 degrees of freedom
Residual Deviance: 39.17989 on 6 degrees of freedom
Number of Fisher Scoring Iterations: 6
_________________________________________________________________________ Also in R. program, here is the same program together with the complain.
name.data=counts (above).
> symmetry
function(i,j,name.data){
A<-(c(1:i))
B<-(c(1:j))
name.data<-expand.grid(A=A,B=B)
name.data$counts<-(c(counts))
name.data$symm<-paste(pmin(as.numeric(name.data$A),as.numeric(name.data$B)),
pmax(as.numeric(name.data$A),as.numeric(name.data$B)),sep=",")
symmetry<-glm(counts~symm,data=name.data,family=poisson(link=log))
}> symmetry(4,4,counts)
Error in model.frame(formula, rownames, variables, varnames, extras, extranames, : invalid variable type
I tried to print out the table with symm pathern. and the function for symm below.
> i<-4 > j<-4 > A<-(c(1:i)) > B<-(c(1:j)) > name.data<-expand.grid(A=A,B=B) > name.data$counts<-(c(counts)) >name.data$symm<-paste(pmin(as.numeric(name.data$A),as.numeric(name.data$B)), + pmax(as.numeric(name.data$A),as.numeric(name.data$B)),sep=",") > name.data A B counts symm 1 1 1 22 1,1 2 2 1 2 1,2 3 3 1 2 1,3 4 4 1 0 1,4 5 1 2 5 1,2 6 2 2 7 2,2 7 3 2 14 2,3 8 4 2 0 2,4 9 1 3 0 1,3 10 2 3 2 2,3 11 3 3 36 3,3 12 4 3 0 3,4 13 1 4 0 1,4 14 2 4 1 2,4 15 3 4 17 3,4 16 4 4 10 4,4 >
> symm
function (x, levels = sort(unique.default(x), na.last = TRUE),
labels = levels, exclude = NA, ordered = is.ordered(x))
{
if (is.null(x))
x <- list()
exclude <- as.vector(exclude, typeof(x))
levels <- levels[is.na(match(levels, exclude))]
f <- match(x, levels)
names(f) <- names(x)
nl <- length(labels)
attr(f, "levels") <- if (nl == length(levels))
as.character(labels)
else if (nl == 1)
paste(labels, seq(along = levels), sep = "")
else stop(paste("invalid labels; length", nl, "should be 1 or",
length(levels)))
class(f) <- c(if (ordered) "ordered", "factor")
f
}----------------------------------------------------------------------------- The model and Assumptions
log(m_ij)= lambda + lambda_i + lambda_j + lambda_ij
where, lambda_ij = lambda_ji for i not equal to j and lambda_i(A) = lambda_i(B) Likelihood equation is
m_ij =(n_ij + n_ji)/2
For symmetry m_(ij)=m_(ji)
"R program" does not recognised "symm" pathern, that is (1,1), (1,2) and so on but "S-plus" do. So please I need your assistance.
Thanks for your usual contibutions.
Yours
Sola.
-- --------------------------------- Adebowale Olusola Adejumo Department of Statistics LMU,University of Muenchen Ludwigstraße 33/III D - 80539 München Germany.
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