similar to: errores

Hola: Si aún hay alguien que no está de vacaciones, igual me pueden ayudar. Quiero ajustar unos modelos: REG_LOG <- glm (low ~ X, family = "binomial", data = DATOS) Ejemplo: library(MASS) data(birthwt, package="MASS") birthwt$low <- factor(birthwt$low) birthwt$race <- factor(birthwt$smoke) REG_LOG <- glm (low ~ smoke, family =

Ben Bolstad experienced something odd while running R CMD check over a package of ours using r-devel (yesterday's fresh). He tracked down the problem to a vignette calling 'library(MASS)'. Please kindly ignore if this is a known (and temporary) issue. Laurent ----- Forwarded message from Ben Bolstad <bolstad@stat.berkeley.edu> ----- Return-Path:

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

Hola Carlos: Gracias por responder! Ayer caí en esta página al buscar el problema con google, pero no conseguir entender y implementar lo que sugiere. Sin entender nada, lo que hice fue: ======================== > library(MASS) > library (sqldf) # Per SQL > data(Aids2, package="MASS") > SQL_PROVA = function (XDADES, XWHE) + { + XDADES_SQL = sqldf ("select * from

Hola Carlos: Te adjunto un ejemplo de aplicación: las funciones (he borrado los path de las funciones y las ordenes "source()" que las carga ) y un ejemplo para ejecutarlas para las opciones que tengo implementadas con la tabla de datos birthwt del paquete"MASS": - Descriptiva de todas las variables de una tabla. - Análisis univariado de todas las variables de una tabla

Dear friends, In R, the help of "bic.glm" tells the difference between postmean(the posterior mean of each coefficient from model averaging) and condpostmean(the posterior mean of each coefficient conditional on the variable being included in the model), But it's still unclear about the results explanations, and the artile of Rnews in 2005 on BMA still don't give more detail on

The birth weight example from ?stepAIC in package MASS runs well as indeed it should. However when I change stepAIC() calls to step() calls I get warning messages that I don't understand, although the output is similar. Warning messages: 1: In model.response(m, "numeric") : using type="numeric" with a factor response will be ignored (and three more the same.) Checked

I'm trying to figure out a good way to smooth binary data. The ideal approach appears to be the "sm.logit" function in library "sm", but I haven't had success with it. Below, is some code illustrating what I've come up with so far, but I'm hoping there is a better approach. I'm using R 1.2 (development) under Windows 98. -Bill library(MASS) data(birthwt)

Dear R users, Thanks in advance. I am Deb, Statistician at NSW Department of Commerce, Sydney. I am using R 2.9.1 on Windows XP. This has reference to the package “MCMCpack”. My objective is to select a better model using various alternatives. I have provided here an example code from MCMCpack.pdf. The matrix of Bayes Factors is: model1 model2 model3 model1 1.000 14.08

Hola: No consigo que la función sqldf () funcione dentro de una función. Alguien puede echarme una mano. En resumen, el problema es que cuando lo ejecuto fuera de una función no tengo ningún problema: ========================== > # install.packages("sqldf") > library(MASS) > library (sqldf) > data(Aids2, package="MASS") > options(digits=3) > table

Thank you ahead of time for help with this. I have two matrices X [,1] [,2] [,3] [,4] [,5] [,6] [1,] 660 693.00 726.0 759.00 792.0 825.00 [2,] 548 575.40 602.8 630.20 657.6 685.00 [3,] 676 709.80 743.6 777.40 811.2 845.00 [4,] 763 801.15 839.3 877.45 915.6 953.75 [5,] 768 806.40 844.8 883.20 921.6 960.00 [6,] 692 726.60 761.2 795.80 830.4 865.00 [7,] 657 689.85 722.7

Greetings, Cohen, Cohen, West, and Aiken 2003 (Applied Multiple Regression-Correlation Analysis for the Behavioral Sciences, Third Edition) on page 273 state the covariance matrix of the regression coefficients is provided by standard programs for multiple regression, including SAS, SPSS, and SYSTAT. How can it be calculated with R. Thank you very much. pbm Peter B. Mandeville cel:

I have a vector Pes with 600 elements some of which are NA's. How can I form a vector of the indices of the NA's. for(i in 1:600) if(is.na(Pes[i])) print(i) prints the indices of the NA's but I can't figure out how to put the results in a vector. Thank you very much. Peter B. -- Peter B. Mandeville mandevip at deimos.tc.uaslp.mx Jefe del Depto. de

Kjetil Halvorsen mentioned a book call "S-Poetry in R". I checked with amazon.com and Barnes and Noble but they don't have it listed. Can somebody please give me the complete reference and where it can be obtained. Suggestion: Might it be possible to put a list of the most important and new literature about R, S, and S+ which has a direct bearing on R in the Documentation section

Hi, Because I'm new to R and trying to move off of SPSS, I have another question. I downloaded the "Foreign" package which I understand reads in various datasets from programs such as SPSS and SAS. There isn't much documentation that I can find regarding the specifics of this in the online docs, but I assume that it is like read.table. So, here is what I wrote and here is

I have three columns of data, Xc, Trt and fish. This was a repeated measures design with 6 measurements taken from each of 5 fish. Xc is the actual measurement, Trt is the treatment, and fish is the fish number. Data can be seen below (hopefully it is in the column format). I would like to look for differences between treatments in a repeated measures format. I used the following code

I have re-labeled tick marks on the x axis. The problem is that by using axes=FALSE, the axes disappears and when they are called back using axis(side=1)..etc. the axis on sides 1 and 2 do not meet at the bottom left corner of the graph. I would also like to have the 3rd and 4th axes in there as well, all meeting in their respective corners. par(mfrow=c(1,2)) gut<-c("Full",

Version: platform = sparc-sun-solaris2.6 arch = sparc os = solaris2.6 system = sparc, solaris2.6 status = status.rev = 0 major = 0 minor = 64.2 year = 1999 month = July day = 3 language = R -- It is unclear to me that the handling of NAs is desirable, and it has problems with names: > z <- c(T,T,NA,F,T) > names(z) <- letters[1:5] > which(z) Error: names attribute

My data is the following: Time Resistance Temperature 5 2000 4 10 2200 8 15 2500 14 20 2900 20 25 3000 29 30 3100 38 35 3500 46 40 3800 47 45 3900 50 50 4000 51 I would like to create a scatter plot with Time on the x axis, Resistance on the y axis and Temperature on a second y axis. I have tried Plot(Time,Resistance,ylim=range(0,4500)

Tengo un problema que me dice: La libreria MASS de R contiene el fichero birthwt.Trabajando sobre estos datos: 1.-Recodifica las variables tal y como aparece en la ayuda sobre este fichero en R. 2.-Analiza e interpreta la posible asociacion estadistica entre las variables low y smoke. ¿Alguien me podria explicar como hacerlo? Ademas, si alguien puede, no entiendo la validacion cruzada, ni la