search for: fitfunct

...only in the degrees of freedom of a ns() spline. I want to use a wrapper function to do this. The models will be of the form y ~ ns(x, df=splineDF) where splineDF is passed as an argument to a wrapper function. This works fine if the regression function is lm(). But with lme(), I get an error. fitfunction() below demonstrates this. Why? KLUDGEfit() below provides a clumsy solution. It turns the lme() command, along with the appropriate value of splineDF, into a text string and then uses eval(parse(text=mystring)). But is there not a more elegant solution? set.seed(5) junk<-data.frame(x=rno...

...d allow me easier fit fast many distributions and check which of the fits performs better. My sample code (that you can of course execute it looks like that) distrList<-list(   "exponential",  "geometric", "log-normal",  "normal", "Poisson") fitfunction<-function(Type,x){     return (list(Type,(fitdistr(x,Type)))) } require(MASS) On<-round(abs(rnorm(10000,sd=100))+5,digits=0) storeOn<-lapply(distrList,fitdistr,x=On) plot(ecdf(On)) str(storeOn) what I am looking now is to plot with the initial dataset plot(ecdf(On)) all the fitted d...

Dear R users, I know one way to see the code for a hidden function, say function_x, is using default.function_x (e.g. summary.default). But how can I see the code for imported packages that have no namespace (in this case Design)? Many Thanks Eleni

John, You can make a local version of bootcov which either: deletes these arguments from the call to fitter, or modify the switch statement to include rq.fit, the latter would need to also modify rq() to return a fitFunction component, so the first option is simpler. One of these days I'll incorporate clustered se's into summary.rq, but meanwhile this seems to be a good alternative. Roger url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Econ...

...gestions on how to get this (what I assume is) data from the .f file into R? Benjamin S data .Data class 8 ?- ? coefficients var loglik score iter linear.predictors residuals means terms n call Design assign na.action fail non.slopes stats method maxtime time.inc units fitFunction center scale.pred x y time surv std.err surv.summary , ? ? ? ? K [ c g d` a? ?? ?? (? -? ?? ?? ;?...

I would like to limit the significant figures of the calibrated parameters determined by genoud() in the Rgenoud package. Below is some example output, where column 1 is model run number, columns 2-7 are the parameter values, and columns 8-12 are model fit statistics. I would like genoud to internally limit parameters to 4 decimal places as shown in this output. It is clear that the function is

Dear all, I had a R segmentation fault, and then invoked debug mode and ran step by step. When I reached "terms(Y~X1*X2*...*X16)", I would then have "segmentation" fault. However, if I just ran this under regular "R interactive" mode, it would be fine though taking long time. My questions are: 1. Is there a known limit of terms for a formula? 2. Why does the

Dear all, I had a R segmentation fault, and then invoked debug mode and ran step by step. When I reached "terms(Y~X1*X2*...*X16)", I would then have "segmentation" fault. However, if I just ran this under regular "R interactive" mode, it would be fine though taking long time. My questions are: 1. Is there a known limit of terms for a formula? 2. Why does the

...8426 10590 16 0 ... ..- attr(*, "names")= chr [1:8] "Obs" "Events" "Model L.R." "d.f." ... $ method : chr "efron" $ maxtime : num 9.95 $ time.inc : num 1 $ units : chr "Day" $ fitFunction : chr [1:2] "cph" "coxph" $ center : num 0.82 $ scale.pred : chr [1:2] "log Relative Hazard" "Hazard Ratio" $ x : num [1:886393, 1:16] 35.1 27.0 56.4 22.5 56.0 ... ..- attr(*, "dimnames")=List of 2 .. ..$ :...