Hi All,
This is my R-version information:---
> version
_
platform i486-pc-linux-gnu
arch i486
os linux-gnu
system i486, linux-gnu
status
major 2
minor 7.1
year 2008
month 06
day 23
svn rev 45970
language R
version.string R version 2.7.1 (2008-06-23)
While calculating partial correlation for a dataset ,i keep getting this
error :--
*Error in solve.default(Szz) :
system is computationally singular: reciprocal condition number =
4.90109e-18*
On using the traceback() function i get this:--------------
> traceback()
10: *.Call("La_dgesv", a, b, tol, PACKAGE = "base")*
9: solve.default(Szz)
8: solve(Szz)
7: pcor.mat(firstvalue, secondvalue, third_var, method, na.rm = T)
6: PartialCorr_Calculation(value1, value2, third_var, method = "pearson",
na.rm = T)
5: Partial(contrld_third_var(rowvalues$matrix1, rowvalues$matrix2,
x <- stringOfItemCategoryToDataFrameOfItemCategory,
item_category_table,
pcor_type <- "ic"), data1, data2, pcor_thirdvar_type <- "all")
4: main()
3: eval.with.vis(expr, envir, enclos)
2: eval.with.vis(ei, envir)
1: source("correlationFP.R")
In pcor.mat function :--
# By using var-cov matrix
pcor.mat <- function(x,y,z,method="p",na.rm=T){
#print("pcor.mat")
x <- c(x)
y <- c(y)
z <- as.data.frame(z)
m<- identical(all.equal(x, y), TRUE)
#print(m)
if( m=="TRUE")
{
print("inside equality-------------------------------")
return(1)
}
if(dim(z)[2] == 0){
stop("There should be given data\n")
}
data <- data.frame(x,y,z)
if(na.rm == T){
data = na.omit(data)
}
xdata <- na.omit(data.frame(data[,c(1,2)]))
Sxx <- cov(xdata,xdata,m=method)
xzdata <- na.omit(data)
xdata <- data.frame(xzdata[,c(1,2)])
zdata <- data.frame(xzdata[,-c(1,2)])
Sxz <- cov(xdata,zdata,m=method)
zdata <- na.omit(data.frame(data[,-c(1,2)]))
Szz <- cov(zdata,zdata,m=method)
# is Szz positive definite?
zz.ev <- eigen(Szz)$values
if(min(zz.ev)[1]<0){
stop("\'Szz\' is not positive definite!\n")
}
# partial correlation
Sxx.z <- Sxx - Sxz %*% solve(Szz) %*% t(Sxz) # this gets printed
rxx.z <- cov2cor(Sxx.z)[1,2] # probably error in this function cov2cor
return(rxx.z)
}
for some other datasets this pcor.mat function works fine.
The solve.default function is this:---------------
solve.default<-function(a, b, tol = ifelse(LINPACK, 1e-07,
.Machine$double.eps),LINPACK = FALSE, ...)
{
if (is.complex(a) || (!missing(b) && is.complex(b))) {
a <- as.matrix(a)
if (missing(b)) {
if (nrow(a) != ncol(a))
stop("only square matrices can be inverted")
b <- diag(1 + (0+0i), nrow(a))
colnames(b) <- rownames(a)
}
else if (!is.complex(b))
b[] <- as.complex(b)
if (!is.complex(a))
a[] <- as.complex(a)
return(if (is.matrix(b)) {
if (ncol(a) != nrow(b)) stop("'b' must be compatible with 'a'")
rownames(b) <- colnames(a)
.Call("La_zgesv", a, b, PACKAGE = "base")
} else drop(.Call("La_zgesv", a, as.matrix(b), PACKAGE = "base")))
}
if (is.qr(a)) {
warning("solve.default called with a \"qr\" object: use 'qr.solve'")
return(solve.qr(a, b, tol))
}
if (!LINPACK) {
a <- as.matrix(a)
if (missing(b)) {
if (nrow(a) != ncol(a))
stop("only square matrices can be inverted")
b <- diag(1, nrow(a))
colnames(b) <- rownames(a)
}
else storage.mode(b) <- "double"
storage.mode(a) <- "double"
return(if (is.matrix(b)) {
if (ncol(a) != nrow(b)) stop("'b' must be compatible with 'a'")
rownames(b) <- colnames(a)
.Call("La_dgesv", a, b, tol, PACKAGE = "base")
} else drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE =
"base")))
}
a <- qr(a, tol = tol)
nc <- ncol(a$qr)
if (a$rank != nc)
stop("singular matrix 'a' in 'solve'")
if (missing(b)) {
if (nc != nrow(a$qr))
stop("only square matrices can be inverted")
b <- diag(1, nc)
colnames(b) <- rownames(a$qr)
}
qr.coef(a, b)
}
So what has to be done in the "base" package to get rid of this error.
--
Thanks
Moumita
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