similar to: why does R stepAIC keep unsignificant variables?

Can someone please help with the error message below? thanks! Start: AIC=-Inf value ~ 1 + Core_CPI__ + GDP_change + Unemployment + housing + interest + S_P + d1 + d2 + d3 Error in if (any(ch)) { : missing value where TRUE/FALSE needed In addition: Warning message: attempting model selection on an essentially perfect fit is nonsense

Hi, Here is the summary-output of the Coxph-model I used (the output is based on the best final model i.e. all significant explanatory variables and their interactions are included): coxph(formula = Y ~ LT + Food + Temp2 + LT:Food + LT:Temp2 + Food:Temp2 + LT:Food:Temp2) n= 555 coef exp(coef) se(coef) z

hello, I am looking for a step() function for GAM's. In the book Statistical Computing by Crawley and a removal of predictors has been done "by hand" model <- gam(y ~s(x1) +s(x2) + s(x3)) summary(model) model2 <- gam(y ~s(x2) + s(x3)) # removal of the unsignificant variable #then comparing these two models if an significant increase occurs. anova(model, model2,

Dear R-gurus, I have an interpretation problem regarding lme models. I am currently working on dog locomotion, particularly on some variation factors. I try to figure out which limb out of 2 generated more dispersed data. I record a value called Peak, around 20 times for each limb with a record. I repeat the records during a single day, and on several days. I tried to build two models, one

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Conditional logistic regression and small sample sizes: what to do? Dear R-Gurus, [I run R 2.8.0 on WinXP. I have no formal training in statistics.] Please feel free to skip the 'Blah blah part' for questions below. - ---Blah blah part-------- Why I use clogit (package 'survival')?: I am looking for risk factors for cases during a

Début du message réexpédié : > De: Depiereux Constant <constant.depiereux@aqte.be> > Date: 16 mars 2005 00:11:11 GMT+01:00 > À: spjgmwn@iop.kcl.ac.uk > Objet: Rép : [R] RODBC, sqlSave and sqlAppend > > > Le 15-mars-05, à 16:19, Matthew W Nash a écrit : > >> Hi all, >> >> I am currently trying to read, write and append data between R and MS

Hi, There is a lot of speex quality estimations. One of this comparative estimation is even available on the official site <http://speex.org/comparison/>. I'd like to present yet another one. And I thought that the best place for this presentation would be Speex-dev mailing list. I want to get feedbacks and criticisms please. If Speex authors consider to make some parts of this work

Dear R Users I am maximizing a user defined log likelihood function. It includes variance parameter (sigma). I used R function optim with BFGS maximization method. However, it stops before the solution saying ?sqrt(sigma): NaNs produced? Could anybody know a proper transformation for sigma which can be passed in the function? For the correlation parameter I used Fishers? transformation so it

Hello, All, How can I maintain the decimal places when using write.table()? Jim e.g. df: EFFECT2 PVALUE 1 0.023 0.88080 2 -0.260 0.08641 3 -0.114 0.45200 write.table(df,file='df.txt',quote=F,sep='\t',row.names=F) df.txt: EFFECT2 PVALUE 0.023 0.8808 -0.26 0.08641 -0.114 0.452 [[alternative HTML version deleted]]

I tried to bootstrap the correlation between two variables x1 and x2. The resulting distribution has two distinct peaks, how should I interprete it? The original code is attached. Y. C. Tao ---------------- library(boot); my.correl<-function(d, i) cor(d[i,1], d[i,2]) x1<-c(-2.612,-0.7859,-0.5229,-1.246,1.647,1.647,0.1811,-0.07097,0.8711,0.4323,0.1721,2.143,

Here is a copy of the last few lines in base-Ex.Rout.fail: > x <- seq(3,500);yl <- c(-.3, .2) > plot(x,x, ylim = yl, ylab="",type='n', main = "Bessel Functions Y_nu(x)") > for(nu in nus){xx <- x[x > .6*nu]; lines(xx,besselY(xx,nu=nu), col = nu+2)} > legend(300,-.08, leg=paste("nu=",nus), col = nus+2, lwd=1) > > x <-

Hi, I receive the following warning message when I run a poisson GLM in R: "glm.fit: fitted rates numerically 0 occurred" The model summary is shown below. The variable 'Species' consists of counts of different species ranging from 0 to 4. I suspect this may have something to do with the warning message but I'm not sure. Can anybody help? Thank you! Anna Call:

Hello, I have spent a good deal of time searching for an answer to this but have come up empty-handed; I apologize if I missed something that is common knowledge. I am trying to figure out how to get an ANOVA table that shows the sum of squares. degrees of freedom, etc, for the full model versus the error (aka residuals). Here is an example of the kind of table I'd like to get:

Dear ReXperts, I have the below text file output. I need to extract the T, QC, QO, QO-QC and WT columns for the data between T = 10 and T=150. Any ideas? Thanks in advance. ======================================================================================== 1 D C ---CAT-- T THETA QC QO QO-QC QC/QO WT FSD 8 1 0 1.0000E+01

I thought I would have another try at explaining my problem. I think that last time I may have buried it in irrelevant detail. This output should explain my dilemma: > dim(S) [1] 1455 269 > summary(as.vector(S)) Min. 1st Qu. Median Mean 3rd Qu. Max. -1.160e+04 0.000e+00 0.000e+00 -4.132e-08 0.000e+00 8.636e+03 > sum(as.vector(S)==0)/(1455*269) [1]

I use lmer to fit a mixed effect model.It give some warnings.what does this warnings mean? and what should I do? > (fm2.mlm <- lmer(qd ~ edu + jiankang + peixun +hunyin + cadcj + age + age2 + sex + dangyuan + Comp.1 + Comp.2+trust.cz1 +(trust.cz1|commid), data = individual,na.action = "na.exclude",family="quasibinomial")) Generalized linear mixed model fit using PQL

Craig, Thanks for your follow-up note on using the asypow package. My problem was not only constructing the "constraints" vector but, for my particular situation (Poisson regression, two groups, sample sizes of (1081,3180), I get very different results using asypow package compared to my other (home grown) approaches. library(asypow) pois.mean<-c(0.0065,0.0003) info.pois <-

Dear Members, Greetings! I have come across a discrepancy shown by R and SAS results on same data for logistics regression.. When I processed the above csv file(1000.csv) for predicting the Action (i/c) by Age Group(1-7,Na) and Gender(M,F,Na) with GLM of R I get: R result Call: glm(formula = Action ~ Gender + AgeGroup, family = binomial, data = mydata1, na.action = na.pass) Deviance

How to select the number of PLS components for GPLS for data sets with few samples? Concrete problem: My data set: 9 samples of class A and 37 of class B with 254 descriptors. In the paper: "Classification Using Generalized Partial Least Squares", Beiying Ding, Robert Gentleman, Bioconductor Project Working Papers, year 2004, paper 5 Section 2.6 Assessing Prediction: Cite:

1 hour spent and I can''t got explanation why I have "execution expired" when I trying to test this web service: Pointed to: http://localhost:3000/news/list class NewsService < ActionWebService::Base web_service_api NewsApi def list [NewsTopic.new, NewsTopic.new] end end class NewsController < ApplicationController wsdl_service_name ''news''