[R] Finding non-normal distributions per row of data frame?

[Patrizio Frederic]

Hi Danny,
it sounds to much easer than that.

Try

y <- data.frame(matrix(rnorm(100),10))
nr <- ncol(y)

test <- lapply(y, shapiro.test)
sapply(test,function(x)c(x$statistic, x$p.value))

it should perform the required task.
Cheers,

P

On Fri, Feb 4, 2011 at 4:52 AM, DB1984 <dannybolg at gmail.com> wrote:
>
> This is my first attempt at this, so hopefully a few kind pointers can get me
> going in the right direction...
>
> I have a large data frame of 20+ columns and 20,000 rows. I'd like to
> evaluate the distribution of values in each row, to determine whether they
> meet the criteria of a normal distribution. I'd loop this over all the rows
> in the data frame, and output the summary results to a new data frame.
>
> I have a loop that should run a Shapiro-Wilk test over each row,
>
> y= data frame
>
> for (j in 1:nr) {
> y.temp<-list(y[j,])
> testsw <- lapply(y.temp, shapiro.test)
> testtable <- t(sapply(testsw, function(x) c(x$statistic, x$p.value)))
>  colnames(testtable) <- c("W", "p.value")
> }
>
>
> but it is currently throwing out an error:
>  "Error in `rownames<-`(`*tmp*`, value = "1") :
>  attempt to set rownames on object with no dimensions"
>
> ...which I guess is unrelated to the evaluation of normality, and more
> likely a faulty loop?
>
> Any suggestions either for this test, or a better way to evaluate the normal
> distribution (e.g. qq-plot residuals for each row) would be greatly
> received. Thanks.
> --
> View this message in context: http://r.789695.n4.nabble.com/Finding-non-normal-distributions-per-row-of-data-frame-tp3259439p3259439.html
> Sent from the R help mailing list archive at Nabble.com.
>
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