similar to: questions on plotting dedrograms

> On Apr 10, 2016, at 3:11 AM, Murray Efford <murray.efford at otago.ac.nz> wrote: > > Martin - > Thanks, but although hatvalues() is useful for calculating PRESS, I can't find anything directly relevant to my question in the influence help pages. After some burrowing in the literature I'm doubting there is an answer out there (PRESS R^2 is always presented in a fairly

Martin - Thanks, but although hatvalues() is useful for calculating PRESS, I can't find anything directly relevant to my question in the influence help pages. After some burrowing in the literature I'm doubting there is an answer out there (PRESS R^2 is always presented in a fairly ad hoc way). This is a new topic, as you say, and perhaps better handled on a statistics list. Murray Efford

> On Apr 10, 2016, at 9:38 AM, David Winsemius <dwinsemius at comcast.net> wrote: > >> >> On Apr 10, 2016, at 3:11 AM, Murray Efford <murray.efford at otago.ac.nz> wrote: >> >> Martin - >> Thanks, but although hatvalues() is useful for calculating PRESS, I can't find anything directly relevant to my question in the influence help pages. After

A package I have written makes considerable use of external C code. There appear to be no problems building a Windows binary with the GNU C compiler, but now I would like to make the package available for other platforms. A stringent check of the code with the gcc options '-Wall -pedantic' flags many nested functions and variable-length arrays that are not allowed in ISO C. Is it

>>>>> Murray Efford <murray.efford at otago.ac.nz> >>>>> on Fri, 8 Apr 2016 18:45:33 +0000 writes: > Thanks for these perfectly consistent replies - I didn't > understand the purpose of m = sum(w * f/sum(w)) and saw it > merely as a weighted average of the fitted values. My > ultimate concern is how to compute an appropriate

Do you mean w <- z$residuals ? Type names(z) to see the list of item in your model. I ran your code on a lm and it work fine. You don't need the brackets around mss <- Michael Long On 04/07/2016 02:21 PM, Murray Efford wrote: > Following some old advice on this list, I have been reading the code for summary.lm to understand the computation of R-squared from a weighted

Thanks for these perfectly consistent replies - I didn't understand the purpose of m = sum(w * f/sum(w)) and saw it merely as a weighted average of the fitted values. My ultimate concern is how to compute an appropriate weighted TSS (or equivalently, MSS) for PRESS-R^2 = 1 - PRESS/TSS = 1 - PRESS/ (MSS + PRESS). Do you think it then makes sense to substitute the vector of leave-one-out fitted

Following some old advice on this list, I have been reading the code for summary.lm to understand the computation of R-squared from a weighted regression. Usually weights in lm are applied to squared residuals, but I see that the weighted mean of the observations is calculated as if the weights are on the original scale: [...] f <- z$fitted.values w <- z$weights [...] m

Announcement: mvtnorm Multivariate Normal and T Distribution mvtnorm implements two R functions for the computation of the multivariate t and normal distribution: pmvt: Computes the the distribution function of the multivariate t distribution for arbitary limits, degrees of freedom and correlation matrices based on algorithms by Genz and Bretz. pmvnorm: Computes the distribution

Announcement: mvtnorm Multivariate Normal and T Distribution mvtnorm implements two R functions for the computation of the multivariate t and normal distribution: pmvt: Computes the the distribution function of the multivariate t distribution for arbitary limits, degrees of freedom and correlation matrices based on algorithms by Genz and Bretz. pmvnorm: Computes the distribution

On 08 Apr 2016, at 12:57 , Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > On 07/04/2016 5:21 PM, Murray Efford wrote: >> Following some old advice on this list, I have been reading the code for summary.lm to understand the computation of R-squared from a weighted regression. Usually weights in lm are applied to squared residuals, but I see that the weighted mean of the

I construct a pdf package manual in Windows 7 using R CMD Rd2dvi --pdf --no-preview [packagename] Page numbers are listed correctly under 'R topics documented' at the front, but incorrectly (offset by -2 pages) in the Index at the back. Following the hyperlinked page numbers in the Index takes you to the wrong page. 2 pages happens to be the length of the package overview man page inserted

Hi, I have been experimenting with the various rsync options and so far have had no luck, so I thought I would ask the experts out there. We have remote devices out in the field and communicate with them via GPRS. I am writing an app that will push new audio files out to remote devices using rsync. The app also periodically uses rsync to grab log files. So here is my scenario: The Remote

Dear All, I have a cluster object based on a dissimilarity matrix from about 1,100 cases and wish to know whether anyone can think of any tips to display some form of graphical output which would give some sense of the similarity between the cases. A standard form of dendrogram would be fine, but with so many cases the dendrogram on the standard devices (R-2.20 on NT4) is very compact

https://bugzilla.netfilter.org/show_bug.cgi?id=1398 Bug ID: 1398 Summary: tproxy rule is not matched for ip6 Product: nftables Version: unspecified Hardware: x86_64 OS: Ubuntu Status: NEW Severity: normal Priority: P5 Component: kernel Assignee: pablo at netfilter.org

I have followed the instructions on how to build a Windows package and everything seems to work EXCEPT that I can't see the data files that I have loaded into the data directory. I have placed the appropriate data in the data directory (as in the instructions). There are 3 data sets, which I can see when I use the command in R. Details below. I have searched everywhere to try to fix this, but

On 07/04/2016 5:21 PM, Murray Efford wrote: > Following some old advice on this list, I have been reading the code for summary.lm to understand the computation of R-squared from a weighted regression. Usually weights in lm are applied to squared residuals, but I see that the weighted mean of the observations is calculated as if the weights are on the original scale: > > [...] > f

Hello, I would like to use my own dissimilarity matrix in a PAM clustering with method "pam" (cluster package) instead of a dissimilarity matrix created by daisy. I read data from a file containing the dissimilarity values using "read.csv". This creates a matrix (alternatively: an array or vector) which is not accepted by "pam": A call

Dear List, This is Elaine, a postgraduate studying in bird distributions in East Asia. I want to calculate Simpson dissimilarity index, based on a presence/absence matrix of bird species in islands in East Asia. (matrix row: 36 islands/matrix column: species ID) (R package vegan to make NMDS and R package betapart) In most papers using vegan for NMDS and betapart for dissimilarity

I'm clustering rather large data sets and would like to cut the dendrograms to get a better view of specific components. I calculate the dissimilarity matrix using daisy() because I have a mixture of variable types: factors, ordered factors and numerical variables. If I want one dendrogram, I use agnes() for the agglomerative nesting and pltree() to draw the dendrogram. That way, I get the