on 09/21/2008 08:01 PM Ted Byers wrote:
> I have a number of files containing anywhere from a few dozen to a few
> thousand integers, one per record.
>
> The statement "refdata18 =
> read.csv("K:\\MerchantData\\RiskModel\\Capture.Week.18.csv", header =
> TRUE,na.strings="")" works fine, and if I type refdata18, I get the integers
> displayed, one value per record (along with a record number). However, when
> I try " fitdistr(refdata18,"negative binomial")", or hist.scott(refdata18,
> prob = TRUE), I get an error:
>
> Error in fitdistr(refdata18, "negative binomial") :
> 'x' must be a non-empty numeric vector
> Or
> Error in hist.default(x, nclass.scott(x), prob = prob, xlab = xlab, ...) :
> 'x' must be numeric
>
> How can it not recognise integers as numbers?
>
> Thanks
>
> Ted
'refdata18' is a data frame and the two functions are expecting a
numeric vector.
If you use:
fitdistr(refdata18[, 1], "negative binomial")
or
hist(refdata18[, 1])
you should get a suitable result, presuming that the first column in the
data frame is a numeric vector.
Use:
str(refdata18)
to get a sense for the structure of the data frame, including the column
names, which you could then use, instead of the above index based syntax.
HTH,
Marc Schwartz
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