similar to: Forward Stepwise regression based on partial F test

I am attempting to develop a multiple regression model using selected model variables that should all be treated as numeric (mostly real) values. However, R considers one specific variable "mass" automatically to be of class "factor", probably because "mass" consists of integer values that are repeated. I now want to force R to treat "mass" as a numeric

oops, Forgot to cc to the list. Regards, Mike -----Original Message----- From: dr mike [mailto:dr.mike at ntlworld.com] Sent: 24 February 2005 19:21 To: 'Spencer Graves' Subject: RE: [R] Bayesian stepwise (was: Forward Stepwise regression based onpartial F test) Spencer, Obviously the problem is one of supersaturation. In view of that, are you aware of the following? A Two-Stage

Dear List members I am using the regsubsets function to select a few predictor variables using Mallow's Cp: > sel.proc.regsub.full <- regsubsets(CO2 ~ v + log(v) + v.max + sd.v + tad + no.stops.km + av.stop.T + a + sd.a + a.max + d + sd.d + d.max + RPA + P + perc.stop.T + perc.a.T + perc.d.T + RPS + RPSS + sd.P.acc + P.dec + da.acc.1 + RMSACC + RDI + RPSI + P.acc + cov.v + cov.a +

Hello I am trying to use all subsets regression on a test dataset consisting of 11 trails and 46 potential predictor variables. I would like to use Mallow's Cp as a selection criterion. The leaps function would provide the required output but does not work with this many variables (see below). The alternative function regsubsets should be used, but I am not able to define the function in

So I recognize that: 1. many people hate forward stepwise regression (i've read the archives)--but I need it 2. step() or stepAIC are two ways to get a stepwise regression in R But here's the thing: I can't seem to figure out how to specify that I want the criteria to be Mallow's Cp (and then to subsequently tell me what the Cp stat is). I know it has something to do with

Hello, The estimate of glm dispersion can be based on the deviance or on the Pearson statistic. I have compared output from R glm() to another statastical package and it appears that R uses the Pearson statistic. I was wondering if it is possible to make use R the deviance instead by modifying the glm(...) function? Thanks for your attention. Kind regards, Robin Smit This e-mail and its

Hello I am able to extract partial regression coefficients from a fitted model object "model", i.e. model <- lm(var.sel.gkm, weights = count.gkm, data = DATA) summary(model) write.table(model$coef, file = "C:/coef_CO_gkm.txt", row.names = TRUE, col.names = TRUE) I was wondering if anyone could advise me how to extract other object items such as std. error, t-values

Hi, Is there any package for logistic model selection using BIC and Mallow's Cp statistic? If not, then kindly suggest me some ways to deal with these problems. Thanks. -- View this message in context: http://www.nabble.com/Stepwise-logistic-model-selection-using-Cp-and-BIC-criteria-tf4464430.html#a12729613 Sent from the R help mailing list archive at Nabble.com.

Dear list members, I apologize for putting this (probably) very basic question on the mailing list. I have scanned through the R website (using search) but did not found an answer. (code included below) A factor matrix is simply extracted (which can then subsequently be exported using write.table) by FACT$loadings[1:6,]. I would also like to specifically extract and export

Thank you all for your (fast) comments. Unfortunately I could not make the advise work: > mass [1] 800 800 800 800 800 800 800 800 800 800 800 800 800 800 800 800 800 800 910 910 910 910 910 910 910 [26] 910 910 910 910 910 910 910 910 910 910 910 910 910 910 1,020 1,020 1,020 1,020 1,020 1,020 1,020 1,020 1,020

Hello, I have got a simple "cosmetic" question. I have created a bar plot with confidence intervals using: barplot(mean, ylim = c(0,0.2), las = 3, space = 0) arrows(1:17 ,X95p_low, 1:17, X95p_high, length = 0.07, angle = 90, code = 3, lty = 1) Unfortunately, the confidence bars align with the right side of the bars and I would like to shift these to the middle of the bars. Is

Dear mailing list member I have got the following question: The function "cor.test(x1, x2)$p.value" computes the statistical significance of the correlation between vectors x1 and x2. However, I have got a data matrix with many variables. Instead of typing in all possible combinations, I was wondering if there is perhaps an R-function that produces a matrix showing the

Hello all, I have a question on manova in R: I'm using the function "manova()" from the stats package. Is there anything like a stepwise (backward or forward) manova in R (like there is for regression and anova). When I enter: step(Model1, data=Mydata) R returns the message: Error in drop1.mlm(fit, scope$drop, scale = scale, trace = trace, k = k, : no 'drop1'

Hi to all, very strange! I tried to debug why imap process takes 100% CPu and it is very slow when I move an email from an imap folder to another imap folder and then I typed: strace -tt -o /log-imap.txt -p <process number> well, during the trace the imap process doesn't crash and it is very fast. If I stop the tracing, I have again the problem and sometimes the crash of the

Good Day, I fit a multivariate linear regression model with 3 dependent variables and several predictors using the lm function. I would like to use stepwise variable selection to produce a set of candidate models. However, when I pass the fitted lm object to step() I get the following error: Error from R: Error in drop1.mlm(fit, scope$drop, scale = scale, trace = trace, k = k, : no

Dear R-Help, My problem/bug came to light,when fitting a linear model using stepwise selection. I'd started with the straightfoward command step(lm(y~., dataset)) This worked fine, but because this starts with all the possible explanatory variables, it results in a model with too many explanatory variables. Hence I wanted to start with just a constant and do forward selection, to get a

 Hi, Is there any function available to do stepwise selection of variables in Conditional(matched) logistic regression( clogit)? step, stepwise  etc are failing in case of conditional logistic regression. Please help.  Thanks P.T. Subha [[alternative HTML version deleted]]

Hi everyone, I am wondering if there exists a stepwise regression function for the Bayesian regression model. I tried googling, but I couldn't find anything. I know "step" function exists for regular stepwise regression, but nothing for Bayes. Thanks -- View this message in context: http://www.nabble.com/Bayesian-regression-stepwise-function--tp26013725p26013725.html Sent from

Sorry, I have wrote a wrong subject in the first email! Regards, Linda ---------- Forwarded message ---------- From: linda Porz <linda.porz@gmail.com> Date: 2011/5/25 Subject: combined odds ratio To: r-help@r-project.org Cc: r-help-request@stat.math.ethz.ch Dear all, I am looking for an R function which does stepwise selection cox model in r (delta chisq likelihood ratio test) similar

Hi, S-PLUS includes the function "stepwise" which can use a variety of methods to conduct stepwise multiple linear regression on a set of predictors. Does a similar function exist in R? I'm having difficulty finding one. If there is one it must be under a different name because I get an error message when I try 'help(stepwise)' in R. Thanks for your help, Andy Taylor