On Sun, Aug 14, 2011 at 10:03 PM, Chintanu <chint...@gmail.com> wrote:
> Hello Josh,
>
> Thank you - that worked. Also, thanks to VIjayan Padmanabhan for your
> effort.
You are quite welcome.
>
> Further, please allow me to ask 2 quick questions:
>
> 1. The default "cor" takes Pearson correlation. How would I change it to,
> say Spearman correlation ? Something like the following doesn't work.
>
>> apply(file[1, 3:10], 1, cor(method = "spearman"), y = LGD)
apply(file[1, 3:10], 1, cor, y = LGD, method = "spearman")
> Error in .Internal(inherits(x, what, which)) : 'x' is missing
>
>
> 2. Is there any function available that can be used to check whether a
> variable is vector, matrix or dataframe ?
is.vector()
is.matrix()
is.data.frame()
HTH,
Josh
>
> Thank you.
>
> regards,
> Chintanu
>
>
> =============================================================
>
> On Mon, Aug 15, 2011 at 2:03 PM, Joshua Wiley <jwiley.ps...@gmail.com>
> wrote:
>>
>> On Sun, Aug 14, 2011 at 8:41 PM, Chintanu <chint...@gmail.com> wrote:
>> > Hello Joshua,
>> >
>> > I could feel that my explanation was bad so far. Now, giving another
>> > effort
>> > here to simplify things :
>> >
>> > I have a dataframe ("file") containing 8 samples (in columns). Those
>> > samples' results (numericals) are available in the dataframe's rows.
>> >
>> > LGD is another vector.
>> >
>> > LGD <- c(11.6, 12.3, 15.8, 33.1, 43.5, 51.3, 67.3, 84.9)
>> >
>> > Now, correlation needs to be found between -
>> >
>> > i) each of the rows of the dataframe, and
>> > ii) LGD
>>
>> Ah, rows, then try:
>>
>> apply(file[1:47321, 3:10], 1, cor, y = LGD)
>>
>> it is basically an implicit for loop that loops through the first
>> argument (your file matrix), row by row, correlating each row with
>> LGD. So:
>>
>> cor(file[1, 3:10], LGD)
>>
>> from 1 to 47321. It is not very efficient, but even on my slow laptop
>> it is a matter of seconds so speed is probably not a big issue unless
>> it is part of a simulation or something. I have a sense that a smidge
>> of clever work with matrices could avoid the apply() call, but its not
>> jumping out at me.
>>
>> Cheers!
>>
>> Josh
>>
>> > Thanks,
>> > Chintanu
>> >
>> >
>> >
>> > ===============================================================
>> >
>> > On Mon, Aug 15, 2011 at 1:12 PM, Joshua Wiley <jwiley.ps...@gmail.com>
>> > wrote:
>> >>
>> >> On Sun, Aug 14, 2011 at 7:21 PM, Chintanu <chint...@gmail.com> wrote:
>> >> > Hi Joshua,
>> >> >
>> >> > SORRY for not making that clear. I wish to have the correlation
>> >> > values
>> >> > between each column of my "file" with the "LGD". For example:
>> >> >
>> >> > cor (Column 1, LGD)
>> >> > cor (column 2, LGD) ... so on.
>> >>
>> >> Okay, you need to make a tractable example. Create or give us data
>> >> where cor(Column1, LGD) works. LGD is a vector of length 8, file is
>> >> probably some sort of matrix or data frame, which you are extracting
>> >> part of, but there are way too many possible ways to repeat,
>> >> transpose, twist, and otherwise manipulate the data into some sort of
>> >> correlatable form (using rep() is not sufficient---that just gives you
>> >> a really long vector).
>> >>
>> >> If you are currently under the impression that it is possible to
>> >> correlate a 47231 x 1 matrix with a vector of length 8, read the
>> >> Wikipedia page so you understand how correlation works:
>> >> http://en.wikipedia.org/wiki/Correlation_and_dependence.
>> >>
>> >> >
>> >> > The first one you have provided is producing an error :
>> >> >
>> >> >> sapply(file[1:47231, 3:10], FUN = cor, y = rep(LGD, 47231), method =
>> >> >> "pearson")
>> >> > Error in FUN(X[[1L]], ...) : incompatible dimensions
>> >> > Cheers,
>> >> > Chintanu
>> >> >
>> >> >
>> >> > ===============================================
>> >> >
>> >> > On Mon, Aug 15, 2011 at 12:09 PM, Joshua Wiley
>> >> > <jwiley.ps...@gmail.com>
>> >> > wrote:
>> >> >>
>> >> >> Hi Chintanu,
>> >> >>
>> >> >> Do you want the correlation of columns 3:10 of file with the y
>> >> >> vector
>> >> >> or do you want a correlation matrix of all variables?
>> >> >>
>> >> >> ## correlation between cols 3:10 and y
>> >> >> sapply(file[1:47231, 3:10], FUN = cor, y = rep(LGD, 47231), method =
>> >> >> "pearson")
>> >> >>
>> >> >> ## correlation matrix
>> >> >> cor(cbind(file[1:47231, 3:10], rep(LGD, 47231)), method = "pearson")
>> >> >>
>> >> >> HTH,
>> >> >>
>> >> >> Josh
>> >> >>
>> >> >>
>> >> >> On Sun, Aug 14, 2011 at 7:02 PM, Chintanu <chint...@gmail.com>
>> >> >> wrote:
>> >> >> > Hi,
>> >> >> >
>> >> >> > I am not sure how to fix the following error.
>> >> >> >
>> >> >> > LGD <- c(11.6, 12.3, 15.8, 33.1, 43.5,
>> >> >> > 51.3,
>> >> >> > 67.3, 84.9)
>> >> >> >
>> >> >> > cor (x=(file [1:47231,3:10]), y= rep (LGD, 47231), method =
>> >> >> > "pearson")
>> >> >> >
>> >> >> > Error in cor(x = (file[1:47231, 3:10]), y = rep(LGD, 47231),
>> >> >> > method =
>> >> >> > "pearson") :
>> >> >> >
>> >> >> > incompatible dimensions
>> >> >> >
>> >> >> >> sessionInfo()
>> >> >> >
>> >> >> > R version 2.13.0 (2011-04-13)
>> >> >> >
>> >> >> > Platform: i386-pc-mingw32/i386 (32-bit)
>> >> >> >
>> >> >> > locale:
>> >> >> >
>> >> >> > [1] LC_COLLATE=English_Australia.1252
>> >> >> > LC_CTYPE=English_Australia.1252
>> >> >> > LC_MONETARY=English_Australia.1252
>> >> >> > LC_NUMERIC=C LC_TIME=English_Australia.1252
>> >> >> >
>> >> >> > attached base packages:
>> >> >> >
>> >> >> > [1] stats graphics grDevices utils datasets methods
>> >> >> > base
>> >> >> >
>> >> >> > loaded via a namespace (and not attached):
>> >> >> >
>> >> >> > [1] tools_2.13.0
>> >> >> >
>> >> >> > Thank you.
>> >> >> >
>> >> >> > Kind regards,
>> >> >> >
>> >> >> > Chintanu
>> >> >> >
>> >> >> > [[alternative HTML version deleted]]
>> >> >> >
>> >> >> > ______________________________________________
>> >> >> > R-help@r-project.org mailing list
>> >> >> > https://stat.ethz.ch/mailman/listinfo/r-help
>> >> >> > PLEASE do read the posting guide
>> >> >> > http://www.R-project.org/posting-guide.html
>> >> >> > and provide commented, minimal, self-contained, reproducible code.
>> >> >> >
>> >> >>
>> >> >>
>> >> >>
>> >> >> --
>> >> >> Joshua Wiley
>> >> >> Ph.D. Student, Health Psychology
>> >> >> Programmer Analyst II, ATS Statistical Consulting Group
>> >> >> University of California, Los Angeles
>> >> >> https://joshuawiley.com/
>> >> >
>> >> >
>> >>
>> >>
>> >>
>> >> --
>> >> Joshua Wiley
>> >> Ph.D. Student, Health Psychology
>> >> Programmer Analyst II, ATS Statistical Consulting Group
>> >> University of California, Los Angeles
>> >> https://joshuawiley.com/
>> >
>> >
>>
>>
>>
>> --
>> Joshua Wiley
>> Ph.D. Student, Health Psychology
>> Programmer Analyst II, ATS Statistical Consulting Group
>> University of California, Los Angeles
>> https://joshuawiley.com/
>
>
--
Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, ATS Statistical Consulting Group
University of California, Los Angeles
https://joshuawiley.com/
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