similar to: about lm

Hi, I'm using read.csv to import a table. But sevel columns are changed to factor variables automatically. They are actually numbers not factor levels. Why this happened? How can I get the correct table? Thanks a lot. Sonia [[alternative HTML version deleted]]

Hi there I'm trying to fit a logistic regression model to data that looks very similar to the data in the sample below. I don't understand why I'm getting this error; none of the data are proportional and the weights are numeric values. Should I be concerned about the warning about non-integer successes in my binomial glm? If I should be, how do I go about addressing it? I'm

http://www.nabble.com/file/p15359204/test.data.csv http://www.nabble.com/file/p15359204/test.data.csv test.data.csv Hi, I have used apply to have certian combinations, but when I try to use these combinations I get the error [Error in eval(expr, envir, enclos) : object "X.GDAXI" not found]. being a novice I donot understand that after applying combination to the data I cant access

Hello, I'm new here, but will try to be as specific and complete as possible. I'm trying to use “lm“ to first estimate parameter values from a set of calibration measurements, and then later to use those estimates to calculate another set of values with “predict.lm”. First I have a calibration dataset of absorbance values measured from standard solutions with known concentration of

Hola: Al tratar de utilizar la función lm R explota, no se si se trata de un problema de mi máquina o me he dado de bruces con un bicho. Después de intentar depurar mi código he probado lo más básico, abrir R (probado en consola y Rkward) y lanzar los ejemplos de lm, esto es lo que me encuentro: ---------- Corte desde la consola ------------------- R version 2.14.0 (2011-10-31) Copyright (C)

Hello, I have a dataframe of say 20 lines with one line per individual. I want to group these 20 individuals by length class (eg. of 5cm) and get the mean value of all the other variables (eg VarA and VarB) for each length class My dataframe is as follow: Length <- 10:30 VarA <- seq(1000,1200,10) VarB <- seq(500,700,10) Data <- cbind(Length,VarA,VarB) And I want to get something

> On 10 Feb 2017, at 14:53, G?ran Brostr?m <goran.brostrom at umu.se> wrote: > > Thanks to all who answered my third question. I learned something, but: > > On 2017-02-09 17:44, Martin Maechler wrote: >> >>>> On 9 Feb 2017, at 16:00, G?ran Brostr?m <goran.brostrom at umu.se> wrote: >>>> >>>> In my package 'glmmML'

hi i have a belkin ups here some setting chmod 0600 /dev/hiddev0 chown nut:root /dev/hiddev0 linux:/home/sonia # /usr/lib/ups/driver/upsdrvctl start Network UPS Tools - UPS driver controller 2.0.4 Network UPS Tools: New USB/HID UPS driver 0.28 (2.0.4) No matching USB/HID UPS found Driver failed to start (exit status=1) linux:/home/sonia # /usr/lib/ups/driver/upsdrvctl -u root start

Dear R'ers, I am fighting with a problem that is driving me crazy. I use "lm" in my user-defined function, but it seems to be looking for weights outside of my function's environment: ### Generating example data: x<-data.frame(y=rnorm(100,0,1),a=rnorm(100,1,1),b=rnorm(100,2,1)) myweights<-runif(100) data.for.regression<-x[1:3] ### Creating function

I'm a bit of an amateur R programmer. I can do simple R scenarios but my handle on complex grammatical issues isn't steady. I have 12 CSV files that I've read into dataframes. Each has 8 columns and over 2000000 rows. Each dataframe has data associated by time component and a date component in the format of: X.DATE and then X.TIME X.DATE is in the format of MMDDYYYY and X.TIME is

In my package 'glmmML' I'm using old C code and linpack in the optimizing procedure. Specifically, one part of the code looks like this: F77_CALL(dpoco)(*hessian, &bdim, &bdim, &rcond, work, info); if (*info == 0){ F77_CALL(dpodi)(*hessian, &bdim, &bdim, det, &job); ........ This usually works OK, but with an ill-conditioned data

I can't figure out why this is returning an NA for the slope in one case, but not in the other. I can tell that R thinks the first case is singular, but why isn't the second? ## Define X and Y ## There are two versions of x ## 1) "as is" ## 2) shifted to start at 0 y = c(58, 57, 57, 279, 252, 851, 45, 87, 47) x1 = c(1334009411.437, 1334009411.437, 1334009411.437,

Hi all, I'm having some difficulty passing arguments into lm() from within a function, and I was hoping someone wiser in the ways of R could tell me what I'm doing wrong. I have the following: lmwrap <- function(...) { wts <- somefunction() print(wts) # This works, wts has the values I expect fit <- lm(weights=wts,...) return(fit) } If I call my function lmwrap, I get

> > On 9 Feb 2017, at 16:00, G?ran Brostr?m <goran.brostrom at umu.se> wrote: > > > > In my package 'glmmML' I'm using old C code and linpack in the optimizing procedure. Specifically, one part of the code looks like this: > > > > F77_CALL(dpoco)(*hessian, &bdim, &bdim, &rcond, work, info); > > if (*info == 0){ > >

Dear R-Representative: I am very new to R and I have to admit that I am not the cleverest of users. So, please bear with me. I have installed R on my Mac OS 8.6. I am interested in eventually using the packages -- many useful ones have been downloaded with the basic R software. I have looked through some of the manuals, however, I have not yet found how to access the commands in these packages.

I've run into a scoping problem in R. I'm calling a function that * creates a formula * calculates a weight vector * calls lm with that formula and weights This fails. Here's a simplified reproduce example: # f works, g doesn't, h is a workaround rm(w) data <- data.frame(y=runif(20), x=runif(20), z=runif(20)) f <- function(k){ w <- data$z^k coef(lm(y~x, data

Dear all, I'm trying to write tabular data to a text file, these data will be the input of a Fortran program. The format needs to be "(i7,2x,7(e15.7,2x))". I have not been able to find a clean way of producing this output with write.table. I searched for a "write.fortran" function similar to read.fortran() in package utils but I couldn't find any. Below is a small

Starting with data from a microarray experiment and I would like to analyse the influence of two factors (age, treatment) on gene expression. Looking through the r-help archives and the web I tried the following: I put my data in a dataframe similar to this one: > example.df <- as.data.frame(matrix(data=runif(32,100,1000), nrow=4, ncol=4)) > example.df <-

Hi All, This is my R-version information:--- > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 7.1 year 2008 month 06 day 23 svn rev 45970 language R version.string R version 2.7.1 (2008-06-23) While calculating partial

> lm2 <- function(...) lm(...) > lm2(mpg ~ wt, data=mtcars) Call: lm(formula = ..1, data = ..2) Coefficients: (Intercept) wt 37.285 -5.344 > lm2(mpg ~ wt, weights=cyl, data=mtcars) Error in eval(expr, envir, enclos) : ..2 used in an incorrect context, no ... to look in Can anyone explain why this is happening? (Obviously this is a manufactured example, but it