search for: residula

hi! i want to change the "robustness weights" used by loess. these are described on page 316 of chambers and hastie's "statistical models in S" book as r_i = B(e_i,6m) where B is tukey's biweight function, e_i are the residulas, and m is the median average distance from 0 of the residuals. i want to change 6m to, say, 3m. is there a way to do this? i cant figure it out from the help files. thanks, rafael

Dear sir, I am fitting a glm with default identity link: model<-glm(timetoacceptsecs~maleage*maletub*relweight*malemobtrue*femmobtrue) the model is overdisperesed and plot model shows a low level of linearity of the residuals. The overdispersion and linearity of residulas on the normal Q-Q plot is corrected well by using: model<-glm(log(timetoacceptsecs)~maleage*maletub*relweight*malemobtrue*femmobtrue)) Boxcox of my model also suggests that the log transformation is what i should do. I ask how i am able to do this by changing the link function or error fam...

...I need the paired-Dummy for the exporter (state1) and importer (state2): g byte city11=0 replace city11=1 if state1==12¦state2==12 (4) I am interesting in residuals for particular city==12. I have the Dummy for City==12 and regress it on Y-Variable. How could I extract from the output in R the residulas for city==12 (1) to plot this residuals and residuals from other regions in boxplot and (2) to etsimate the confidence interval. Thanks very much in advice, Susan --------------------------------- [[alternative HTML version deleted]]

...vary apart of adding a constant term. The source code of the leaps-package states the package calculates the BIC this way: bicvec<-c(bicvec,(n1+ll$intercept)*log(vr)+i*log(n1+ll$intercept)) with: ## number of observations - Intercept: n1<-ll$nn-ll$intercept ## fraction of sum of squared residulas model i ## and sum of squared residuals null model, I ## just can't understand why the vector ll$ress ## is subscripted double vr<-ll$ress[i,j]/ll$nullrss ## maximum number of variables i ^^ This seems to match the calculation done by extractAIC but it doesn't! Maybe anyone can tell m...

It seems that the standardized deviance residulas, that one gets on plots of a glm.object x with plot(x) are calculated as r <- residuals(x) s <- sqrt(deviance(x)/df.residual(x)) w <- weights(x) hii <- lm.influence(x)$hat r.w <- if (is.null(w)) r else (sqrt(w) * r) rs <- r.w/(s * sqrt(1 - hii)) This implies that, for example...

...e post a reply yet so thought I'd throw in my thoughts. I'm no R expert! When you talk about an exponential trend line are you refering to: 1) y=ax^b or 2) y=ae^(bx) If 1) then take base10 logs of y and x and then fit them with simple linear regression. Then calculate the antilog of the residulas and plot these as your trendline. If 2) then take natural logs of y and x and follow the rest of the procedure described in 1). Hope this helps. Murray M Cooper, Ph.D. Richland Statistics 9800 N 24th St Richland, MI, USA 49083 Mail: richstat at earthlink.net ----- Original Message ----- From:...

Hi all, I have a dataset which consists of 2 columns. I'd like to plot them on a x-y scatter plot and fit an exponential trendline. I'd like R to determine the equation for the trendline and display it on the graph. Since I am new to R (and statistics), any advice on how to achieve this will be greatly appreciated. Many thanks, Chris -- View this message in context: