similar to: lda() - again.

Hello, For a simple problem with 1 predictor (x) and 2 classes (0 and 1), the linear discriminant function should be something like 2(mu_0 - mu_1)/var x + x-independent-terms where var is the common variance.

Hi, I'm running the latest version of R on a linux box. plot() does produce a grahpics window. But is it "normal" for that window to not respond to a left or right mouse click? What I'm really trying to do is the save the graphics to a postscript file, but postscript() produces an "empty postscript file". Thanks, Caren -- http://www.nhn.ou.edu/~marzban

Hi All, I'm having trouble with the colors on my screen getting translated to the colors in the outputted .pdf document. Here is a caricature of my problem: par(mfrow=c(1,1)) x1 = rnorm(1000) x2 = rnorm(1000)+10 y1 = rnorm(1000)+10 y2 = rnorm(1000)+10 palette(rainbow(6)) plot(x=x1,y=y1,col=y1,xlim=c(-10,20)) palette(heat.colors(6)) points(x=x2,y=y2,col=y2) dev.copy2pdf(file =

Im intending use Ext3 file system in my web farm. Im using RedHat 6.2 (kernel 2.2.16-3) and Turbo Linux Cluster Server 6.0. I have NO SUCCESS in path my own kernel. I downloaded the following ext3 packages: ext3-0.0.2f.tar.gz (linux-2.2.16-3.kdb.diff , linux-2.2.16-3.ext3.diff ) e2fsprogs-1.20-0.WIP.i386.rpm e2fsprogs-1.20-0.WIP.src.rpm e2fsprogs-1.20-0ext3.i386.rpm

http://bugzilla.mindrot.org/show_bug.cgi?id=1308 Summary: pam handling change breaks pam_abl module Product: Portable OpenSSH Version: 4.6p1 Platform: UltraSparc OS/Version: Solaris Status: NEW Severity: normal Priority: P2 Component: PAM support AssignedTo: bitbucket at mindrot.org

Warren Young wrote: > On Dec 9, 2015, at 11:55 AM, m.roth at 5-cent.us wrote: >> Matthew Miller wrote: >>> On Wed, Dec 09, 2015 at 01:05:15PM -0500, m.roth at 5-cent.us wrote: >>>>>> >>>> So, you're saying that end users need to go poke their noses into the >>>> development process >>> >>> If you want to go out of

I used the "lda" function in the MASS library of S-Plus (R) to do a linear discriminant analysis, and got the linear coefficients, say b1 and b2 for the 2 predictors x1 and x2. I have trouble to calculate the discrimiant scores for each observation, I used 3 ways to try to repeat the scores returned by the "predict" function in S-Plus: 1. b1*x1+b2*x2 2. b1*(x1-mean of

Dear Users, I am new to both of things, so do not blame me too much... I am busy with semiparametric regression and use WinBUGS to sample posteriors. The code to call Winbugs is as follows: data <- list("y","X","n","m") #My variables inits.beta <- rep(0,K) inits.beta0 <- 0 inits <-

Hello, I'm interested in doing Bayesian kriging using R. I see that the package geoR has a function that will allow one to do this (krige.bayes). However, my data are not in the form of points, but rather they are blocks that represent spatial averages (i.e., the number of fishing hooks per month in a given lat x long square). I am therefore interested in treating the data as

I've sometimes thought it would be useful to have another mail list called "no I haven't read the documentation but someone can save me a lot of time," or perhaps just "newbie" for short. This can be very useful for people just getting started in R and with school starting soon I expect the help list may become overwhelmed. Of course, I think that people should read all

Dear List, I'm using GAMs in a multiple imputation project, and I want to be able to combine the parameter estimates and covariance matrices from each completed dataset's fitted model in the end. In order to do this, I need the knots to be uniform for each model with partially-imputed data. I want to specify these knots based on the quantiles of the unique values of the non-missing

Hi, I run R 2.10.1 under ubuntu 10.04 LTS (Lucid Lynx) and klaR version 0.6-4. I compute a model over a 2 classes dataset (composed of 700 examples). To that aim, I use the function NaiveBayes provided in the package klaR. When I then use the prediction function : predict(my_model, new_data). I get the following warning : "In FUN(1:747[[747L]], ...) : Numerical 0 probability with

In http://advogato.net/person/rakholh/diary.html?start=165 Ali wrote: > For same reason I am arguing with people on vorbis-dev - but I don't > understand what the argument is about (considering that the vorbis > developers proposed a solution which mjs and I thought was reasonable, > and then some developers decided to criticize us again for no reason). Goodness, get dropped

Full_Name: Ross Boylan Version: 2.2.0 OS: Linux Submission from: (NULL) (65.175.48.58) \eqn{{\bf\beta}_j}{b(j)} in my .Rd file produces this error -------------------------------------------- ! Missing $ inserted. <inserted text> $ l.7 \eqn{{\bf\beta}_j}{\bf\beta}_ jnormal-bracket5bracket-normal{b(j)} -- ! Missing $ inserted. <inserted

I'm seeing various things fail when I try to next braces inside \eqn. This source \eqn{{\bf\beta}_j}{b(j)} is the vector produces this error ---------------------------------------------- [4] ! Missing $ inserted. <inserted text> $ l.258 \eqn{{\bf\beta}_j}{\bf\beta}_ j{{b(j)} is the vector of coefficients fo... I've inserted a

I'm not sure who is responsible for quantile(), but I assume they read this list. Ivan Frohne and I have produced a revision of the quantile.default() function which enables the computation of alternative sample quantile definitions. The code and .Rd file are attached. This enables the user to produce quantiles that are equivalent to those in various statistics package. There is a type

Hi, I am doing a small experiment to test if I can use MathJax ( official site: http://www.mathjax.org ) in R's html help pages (i.e. options(help_type='html')) and it seems working with some minor modifications. The screenshot (rendered by Firefox 4.0 beta and with STIX fonts) of the help page in html format with MathJax enabled is at the following url:

Surprisingly, I played around with some test code and below actually creates equations that look correct. tempmat<-matrix(10,nrow=6,ncol=6) restrictmat<-diag(6) colnames(tempmat)<-c("AUD.l1","CHF.l1","CAD.l1","GBP.l1","EUR.l1","JPY.l 1")

> On Dec 13, 2016, at 11:08 AM, Rui Ueyama <ruiu at google.com> wrote: > > On Tue, Dec 13, 2016 at 11:02 AM, Mehdi Amini <mehdi.amini at apple.com <mailto:mehdi.amini at apple.com>> wrote: > >> On Dec 13, 2016, at 10:06 AM, Rui Ueyama <ruiu at google.com <mailto:ruiu at google.com>> wrote: >> >> On Tue, Dec 13, 2016 at 9:28 AM, Mehdi

I've been working on a new package and I have a few questions regarding the behaviour of the nlm function. I've been (for better or worse) using the nlm function to fit a linear model without suppling the hessian or gradient attributes in the objective function. I'm curious as to why the nlm requires 31 iterations (for the linear model), and then it doesn't work when I try to add