R help - Jun 2009 - Error: system is computationally singular: reciprocal condition number

I get this error while computing partial correlation.


*Error in solve.default(Szz) :
  system is computationally singular: reciprocal condition number 4.90109e-18*

Why is it?Can anyone give me some idea ,how do i get rid it it?

This is the function i use for calculating partial correlation.


pcor.mat <- function(x,y,z,method="p",na.rm=T){


    x <- c(x)
    y <- c(y)
    z <- as.data.frame(z)



    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)

    print(Sxx.z) # this gets printed

    rxx.z <- cov2cor(Sxx.z)[1,2] #some problem in this function
function (V)
    {
       print("cov2cor")
       p <- (d <- dim(V))[1]
        if (!is.numeric(V) || length(d) != 2L || p != d[2L])
            stop("'V' is not a square numeric matrix")
        Is <- sqrt(1/diag(V))
        if (any(!is.finite(Is)))
            warning("diag(.) had 0 or NA entries; non-finite result is
doubtful")
        r <- V
        r[] <- Is * V * rep(Is, each = p)
        r[cbind(1L:p, 1L:p)] <- 1
        r
    }
    return(rxx.z)
}

-- 
Thanks
Moumita

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Your covariance matrix Szz is not positive definite.   It is singular.  The
following test that you are doing is neither necessary nor useful:

    zz.ev <- eigen(Szz)$values
    if(min(zz.ev)[1]<0){

        stop("\'Szz\' is not positive definite!\n")
    }


You may want to use Moore-Penrose inverse, also known as generalized inverse
or pseudoinverse to overcome this problem.  This approach uses
singular-value decomposition (SVD).  Take a look at the "corpcor"
package.

Ravi.

----------------------------------------------------------------------------
-------

Ravi Varadhan, Ph.D.

Assistant Professor, The Center on Aging and Health

Division of Geriatric Medicine and Gerontology 

Johns Hopkins University

Ph: (410) 502-2619

Fax: (410) 614-9625

Email: rvaradhan at jhmi.edu

Webpage:
http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.h
tml

 

----------------------------------------------------------------------------
--------


-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On
Behalf Of Moumita Das
Sent: Thursday, June 25, 2009 10:59 AM
To: r-help at r-project.org
Subject: [R] Error: system is computationally singular: reciprocal
conditionnumber

I get this error while computing partial correlation.


*Error in solve.default(Szz) :
  system is computationally singular: reciprocal condition number 4.90109e-18*

Why is it?Can anyone give me some idea ,how do i get rid it it?

This is the function i use for calculating partial correlation.


pcor.mat <- function(x,y,z,method="p",na.rm=T){


    x <- c(x)
    y <- c(y)
    z <- as.data.frame(z)



    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)

    print(Sxx.z) # this gets printed

    rxx.z <- cov2cor(Sxx.z)[1,2] #some problem in this function function (V)
    {
       print("cov2cor")
       p <- (d <- dim(V))[1]
        if (!is.numeric(V) || length(d) != 2L || p != d[2L])
            stop("'V' is not a square numeric matrix")
        Is <- sqrt(1/diag(V))
        if (any(!is.finite(Is)))
            warning("diag(.) had 0 or NA entries; non-finite result is
doubtful")
        r <- V
        r[] <- Is * V * rep(Is, each = p)
        r[cbind(1L:p, 1L:p)] <- 1
        r
    }
    return(rxx.z)
}

--
Thanks
Moumita

	[[alternative HTML version deleted]]

______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

I get this error .... on using the, traceback() function
:--
> 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")

what is this error ".*Call("La_dgesv", a, b, tol, PACKAGE =
"base")*"  how
can i rectify it?
I don't know statistics...going mad ,debugging this problem..
any help is highly appreciated !! :)

Thanks in advance
Moumita

On Thu, Jun 25, 2009 at 8:29 PM, Moumita Das
<das.moumita.online@gmail.com>wrote:
>
> I get this error while computing partial correlation.
>
>
> *Error in solve.default(Szz) :
>   system is computationally singular: reciprocal condition number >
4.90109e-18*
>
> Why is it?Can anyone give me some idea ,how do i get rid it it?
>
> This is the function i use for calculating partial correlation.
>
>
> pcor.mat <- function(x,y,z,method="p",na.rm=T){
>
>
>     x <- c(x)
>     y <- c(y)
>     z <- as.data.frame(z)
>
>
>
>     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)
>
>     print(Sxx.z) # this gets printed
>
>     rxx.z <- cov2cor(Sxx.z)[1,2] #some problem in this function
> function (V)
>     {
>        print("cov2cor")
>        p <- (d <- dim(V))[1]
>         if (!is.numeric(V) || length(d) != 2L || p != d[2L])
>             stop("'V' is not a square numeric matrix")
>         Is <- sqrt(1/diag(V))
>         if (any(!is.finite(Is)))
>             warning("diag(.) had 0 or NA entries; non-finite result is
> doubtful")
>         r <- V
>         r[] <- Is * V * rep(Is, each = p)
>         r[cbind(1L:p, 1L:p)] <- 1
>         r
>     }
>     return(rxx.z)
> }
>
> --
> Thanks
> Moumita
>


-- 
Thanks
Moumita

	[[alternative HTML version deleted]]