similar to: Grouped regression

Hello, I am new to R and have a couple of questions. My data set contains the variables "Bwt" and "Hwt", which are bodyweight and heartweight, respectively, of a group of cats. With the following code, I am making two plots, both to be viewed in the same plot window in R: library(MASS) maleData <- subset(cats, Sex == "M") linreg0 <- lm(maleData$Hwt ~

Hello, The dataset "cats" contain information about the heart weight ("Hwt"), body weight ("Bwt") and gender ("Sex") of a group of 144 cats. I write the following piece of code: library(MASS)attach(cats)ratio <- Hwt/Bwtmale <- ratio[Sex == "M"]female <- ratio[Sex == "F"] My question is, when I look at the object

Hi: I am trying to create a dynamic latex table using \Sexpr{} but it's not evaluating it. I also tried the example below without Sweave and also fails. I have also copied the Sweave.sty to my working directory but nothing seems to work. Do I need to have certain package in order to run \Sexpr{}? \documentclass[a4paper]{article} \usepackage{C:/R/R-2.8.1/share/texmf/Sweave} \begin{document}

Full_Name: Soren Feodor Nielsen Version: 2.5.0 OS: linux-gnu Submission from: (NULL) (130.225.103.21) The print-out of xtable in the following example is wrong; instead of yielding the correct ci's for the second model it repeats the ci's from the first model. require(xtable) require(MASS) data(cats) b1<-lm(Hwt~Sex,cats) b2<-lm(Hwt~Sex+Bwt,cats)

Hola Tengo un problema con Sweave y xtable, concretamente quiero cambiar el color según un criterio, creo que es más fácil explicar con los siguientes ejemplos, uno puede correr directamente porque es R, al siguiente código hay que guardarlo como Rnw, y luego puede ser corrido en R, donde seguramente al correr este se darán cuenta de mis dos problemas porque saltan al abrir el pdf que se obtiene

Dear List-Members, I have a problem with the function lqs() from package MASS. In some cases it produces different results for the same settings and needs a random seed to be set, in other cases not. I really cannot understand, why this happens. As well I do not understand what exactly you need the random seed for. Is it a starting point for iterations? Or do different results occur because of

Dear all, I'm a trainee statistician in a company and we'd like to understand svm mechanism, at first with simple examples. I use e1071 package and I have several questions. I'm working with data extracted from cats data (from R). My dataset corresponds to a completely separable case with a binary response variable ( Sex with 2 levels: F and M), two explanatory variables (Bwt

Yes, that will halve the number of multiplications. If you?re looking for such optimisations then you can also consider ifelse(G=='male', 65L, 58L). That will definitely use less time & memory if WC is integer, but the trade-offs are more complicated if WC is floating point. Regards, Jorgen Harmse. From: avi.e.gross at gmail.com <avi.e.gross at gmail.com> Date: Friday,

Dear All, For logistic regression models: is it possible to use validate (rms package) to compute bias-corrected AUC, but have variable selection with AIC use step (or stepAIC, from MASS), instead of fastbw? More details: I've been using the validate function (in the rms package, by Frank Harrell) to obtain, among other things, bootstrap bias-corrected estimates of the AUC, when variable

I simply put, > NEVER=subset(infants$bwt,ISNO1) > UNTILPREGNANT=subset(infants$bwt, ISNO2) > ONCENOTNOW=subset(infants$bwt, ISNO3) and I wanna combine those three. I do it like ISNO=NEVER&UNTILPREGNANT&ONCENOTNOW and R tells me 1: In NEVER & UNTILPREGNANT : longer object length is not a multiple of shorter object length 2: In NEVER & UNTILPREGNANT & ONCENOTNOW

Hello all I have what seems like a simple question but have not been able to find an answer on the forum. I'm trying to define a function which involves regression models and a large number of covariates. I would like the function to accept any number of covariates and, ideally, I would like to be able to enter the covariates in a group (e.g. as a list) rather than individually. Is there any

Dear all, as a follow-up to the question asked on R-package-devel (see link below): Someone sent a package to CRAN with a few problems. There's more things wrong with the submission, but one thing that really caught my eye was the following error: Warning message: running command '"C:/PROGRA~1/R/R-33~1.2/bin/x64/R" CMD BATCH --vanilla "testthat.R"

Greetings R users! I am working with the ENSEMBLE climate data (10 min resolution daily temperatures images for all of Europe 1950-2006). The data comes packaged in a single netCDF file. I would like to read the data in and export a subset (2002-2006) as geotiffs (one image per day). So far, I can successfully read in the data and view the images within an R display window. However, I have yet to

Bellow, follows a proposal for a new opensolaris project. Of course, this is open to change since I just wrote down some ideas I had months ago, while researching the topic as a graduate student in Computer Science, and since I''m not an opensolaris/ZFS expert at all. I would really appreciate any suggestion or comments. PROJECT PROPOSAL: ZFS Compression Algorithms. The main purpose of

Just a minor point in the suggested solution: df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG)) since WC and TG are not conditional, would this be a slight improvement? df$LAP <- with(df, TG*(WC - ifelse(G=='male', 65, 58))) -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of Jorgen Harmse via R-help Sent: Friday,

R developers, 2 things: a bug in model.frame and a question about setup of generic functions. I don't understand the following behavior for generic functions: Suppose I'm working with the cats data in the MASS library and I want to create a formula object to model Hwt on Sex: # This works: > formula(Hwt ~ Sex) Hwt ~ Sex # But the following does not: > formula(Hwt ~ Sex,

I might have factored the gender. I'm not sure it would in any way be quicker. But might be to some extent easier to develop variations of. And is sort of what factors should be doing... # make dummy data gender <- c("Male", "Female", "Male", "Female") WC <- c(70,60,75,65) TG <- c(0.9, 1.1, 1.2, 1.0) myDf <- data.frame( gender, WC, TG ) #

df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG)) That will do both calculations and merge the two vectors appropriately. It will use extra memory, but it should be much faster than a 'for' loop. Regards, Jorgen Harmse. ------------------------------ Message: 8 Date: Fri, 3 Nov 2023 11:10:49 +1030 From: "Md. Kamruzzaman" <mkzaman.m at gmail.com>

Dear R'sians, Would really appreciate if you could suggest a more efficient way to order the columns of a dataset. The column names of the dataset contain indices separated by a period. Following are examples of my code and the dataset. oC <- function(tg=x2) { lth <- length(grep("T",names(tg))) thix <-

Hi, I have a question about the usage of eval(). Wonder if any experienced user can help me out of it. I use eval() in the following function: semireg.pwl <- function(coef.s=rnorm(1),coef.a=rnorm(1),knots.pos=knots.x,knots.ini.val=knots.val){ knotn <- length(knots.pos) def.par.env <- sys.frame(1) print(def.par.env) print(environment(coef.s)) tg <- eval( (parse(text=