[R] strange PREDICTIONS from a PIECEWISE LINEAR (mixed) MODEL

Hi Dears, When I introduce an interaciton in a piecewise model I obtain some quite unusual results. If that would't take u such a problem I'd really appreciate an advise from you. I've reproduced an example below... Many thanks x-rnorm(1000) y-exp(-x)+rnorm(1000) plot(x,y)

[R] PREDICTIONS from a PIECEWISE LINEAR (mixed) MODEL: THEY AIN'T LINEAR BETWEEN BREAK POINTS!!

is not straight at all, instead behaves like if it was a hig order polynomial or something similar I attach the codes below, hoping someone can point me the mistake I sincerely express many thanks in advance .. Federico Bonofiglio frame3-data.frame(id,chol,cd4,rt,sex,age, nadir,pharmac2,hbs

[R] glht{multcomp} : use with lme {nlme}

Hi dears, I do CHOL-lme(chol~rt*cd4+sex+age+rf+nadir+pharmac+factor(hcv)+factor(hbs)+ haartd+hivdur+factor(arv), random= ~rt|id, na.action=na.omit) ...runs sweet,..then try a multicomparisons approach for the categorical rf summary(glht(CHOL, linfct=mcp(rf=Tukey))) * Error in

[R] intervals {nlme} lower CI greater than upper CI !!!????

Hi folks... check this out.. GLU-lme(gluc~rt*cd4+sex+age+rf+nadir+pharmac+factor(hcv)+factor(hbs)+ + haartd+hivdur+factor(arv), + random= ~rt|id, na.action=na.omit) intervals(GLU)$fixed lower est. upper (Intercept) 67.3467070345 7.362307e+01

[R] random interaction effect in lmer

Hi dears while modeling an interaction random effect in lmer i receive the instantaneous error message ldlM4-lmer(ldl~rt*cd4+age+rf+pharmac+factor(hcv)+ + hivdur+(rt:cd4|id),na.action=na.omit,REML=F) *Warning message: In mer_finalize(ans) : false convergence (8) * I think the matter lies in

[R] TRADUCING lmer() syntax into lme()

nesting structure that sets factorA1 and factorA2 as same level effects (hence non nested) and factorB as nested in both. I also must express my momentaneous sheer ignorange on the pdMat objects, thing that prabably is not helping me in the process Kindly Regards Federico Bonofiglio

Re: [R] piecewise regression

guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code, as it says in the signature block for each email on this list. Hope this helps. Spencer Graves On 1/14/2011 6:42 AM, Federico Bonofiglio

[R] piecewise regression

Hello everybody Quick question, if you'd like to throw a little tip: does anyone knows a function that runs piecewise regression models with coefficients estimation and inferences ? Thank you [[alternative HTML version deleted]] __

[R] graphics: 3D regression plane

if someone would give me some suggestions. Thank u again and happy new year Federico Bonofiglio [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting

[R] logistic regression with response 0,1

dramatically (one per cell) , so may I risk to never obtain a significant result? I also take the chance to ask wheater u know any implemented method to plot logistic curves directly out of a glm() model I would like to thank u all by the way Federico Bonofiglio [[alternative HTML version

[R] anomalies with the loess() function

Hello Masters, I run the loess() function to obtain local weighted regressions, given lowess() can't handle NAs, but I don't improve significantly my situation.., actually loess() performance leave me much puzzled I attach my easy experiment below

[R] lowess() won't handle NAs

Dear Masters, I'm driving crazy with the lowess() function my intent is smoothing confidence intervals for predicted y values in a linear model lm() setting since in the predict() function there exists an option for predicting NA values, I instead encounter problems when I fit a missing

[R] dpois().......bizarre warning messages

Dear Masters, I have a question to submit consider the following script m-4.95 obs-rpois(36,m) # i generate 36 realization from a poisson(m) hist(obs,freq=F) curve(dpois(x,m),add=T,col=red) #i wish to overlay on the histogram the theorical poisson density function errors are returned saing

[R] the sample() function

the algorithm (or source code? is it right?) behind the *sample()* function, so i can inspect in detail the mechanism of this so gossiped radomization? thank you, sincerely federico bonofiglio, student of statistics at milano bicocca university, italia [[alternative HTML version deleted

[R] cycling k times a realization of a random walk.....problems..

hello R-masters. i have an R-issue here that i don't know if you'd wish to help me  about it: briefly i'd like to generate many (say hundred) realizations of a random walk, execute a few operations on each of them (mean time of return), and graph each realization on the same plot. IN OTHER