similar to: Problem with R INSTALL locfit on DEC alphaev56-dec-osf4.0d

Dear all, after building the R-1.1.1 from source on our alpha everything seems to work, but locfit still hangs... I installed locfit with install.packages(...), the installation process went fine, but calling locfit() blocks the R environment. Has anybody got an idea howto get to the roots of this problem? Thanks M. Eger -- +------------------------------------------------------- | Marcus

Hello, Here is a problem I have had trying to install locfit, the package for R. I have already contacted Clive Loader who thinks the problem has more to do with R than locfit, so here is the point : The version of R I am currently running is R-base-0.90 that I installed using the R-base-0.90.1-1.i386.rpm package. I dowloaded the locfit package available at the CRAN site and ran : R INSTALL

I have some slight problems getting R to run smoothly on our alpha... What might be the reason for the following error message? > postscript() Error in PS(file, old$paper, old$family, old$bg, old$fg, old$width, old$height, : unable to start device PostScript I have compiled R-1.1.1 and it starts without complaint. -- +------------------------------------------------------- |

I was wondering if someone could help me with a problem getting locfit running. I am running Digital Unix 3.2D on an alphastation, with R 0.61.1 I downloaded the CRAN distribution of locfit. I had no problems installing it with R INSTALL (I installed it into my library rather than the default base library; the output is attached at the end of this email message). I then tried to test it with the

I just copy parts of my correspondence with the author of Locfit: >>Dear Mr <...>, >>I have tried to apply locfit to a three dimensional data set for density >>estimation. >>The algorithm seems to work well but when I want to plot the result, the >>routine "levelplot" is missing. >>This is not the case in 2-dimensional fitting. >>I=B4d be

Dear all, I am trying to include confidence intervals in a xyplot. This is what I am doing: xyplot(x ~ y|z, alpha = 1,band = "global",panel = panel.locfit) (more specifically, in my case x is a binary response from a logistic regression model) The output plot was fine but it did not include the confidence intervals Anyone knows how to do it? (xYplot did not work either) many thanks

Hello!!! I'm just a beginner of R. I work with locfit to get the density from an numeric vector. It looks good when I plot the graph, but I need the output data of locfit. For example I need somthing like that (only integer values for the input): numeric vector (input of locfit) density (output of locfit) 1 0.05.... 2 0.04.. 3 0.01 ... Thank you for your help and your time.

Hi All, In another thread Andy Liaw, who CRAN lists as locfit maintainer; said: <quote> From: "Liaw, Andy" <andy_liaw at merck.com> To: "Guy Green" <guygreen at netvigator.com>; <r-help at r-project.org> Subject: Re: Alternatives to linear regression with multiple variables Date: 22 February 2010 17:50 You can try the locfit package, which I believe

Dear R users, i am using locfit package developed by loader in R software, my problem is that as i am doing independont forecast using locfit object , i am able to do independont forecast for more than one years simultaniously. But when i am doing one year forecast(single) this code is giving following error... "Warning message: 'newdata' had 1 rows but variable(s) found have 24

Hello there, I am presently using the locfit package in "R" and would appreciate some help here. Could anyone tell me tell me how I can obtain the various components (x and y values)of the density estimation after using the "R" command "locfit"? For example, with the command "fhat<-density(somename)" I can obtain the x and y values by simply calling

Hi, I?m trying to combine the Locfit Package with the Mgcv package (to use Generalized Additive Models with Locfit components). I read the book written by Clive Loader where it?s said that, for the S language, you just have to "load" the locfit package using the command : Library(locfit, first="T") in order to use locfit components in an additive model. But I can?t. I guess

Dear memberships, I'm trying to estimate the following multivariate local regression model using the "locfit" package: BMI=m1(RCC)+m2(WCC) where (m1) and (m2) are unknown smooth functions. My problem is that once I get the regression done I cannot get the fitted values of each of this smooth functions (m1) and (m2). What I write is the following library(locfit) data(ais)

The locfit library is now available through CRAN, in the Contributed R Code directory. Locfit fits local regression, likelihood and density estimation models, in the spirit of loess but with many additional features. To install, unpack the locfit_19980309.tar.gz file, and R INSTALL locfit Most of the functionality and examples on my home page http://cm.bell-labs.com/stat/project/locfit/ should

The locfit library is now available through CRAN, in the Contributed R Code directory. Locfit fits local regression, likelihood and density estimation models, in the spirit of loess but with many additional features. To install, unpack the locfit_19980309.tar.gz file, and R INSTALL locfit Most of the functionality and examples on my home page http://cm.bell-labs.com/stat/project/locfit/ should

Hi list, This was asked a couple of years ago but I can't find a resolution. Is there any way to get the coefficients from one of the local polynomial fits in locfit. I realize that locfit only constructs polynomials at a handful of intelligently selected points and uses interpolation to predict any other points. I would like to know the terms of the polynomials at these points. It seems

Dear R experts, We've been playing with the locfit package and are experiencing a problem I am hoping for some help on. We have a dataset of 13k points, one dimension of which is "judgment", either 0 or 1, and the other "score", an arbitrary scalar (in this case it's between .65 and .85). We use

I've been trying to run locfit on data with 6 inputs and 1 output in R. Whenever I make a prediction for the same exact data that the model was built on though, I get significant discrepancies between the fitted outputs of the prediction and the actual data. I have scaled the inputs, tweaked the alpha parameter, and played around with a lot of the other variables as well. Is their some kind

Dear R-users, One of the main reasons I moved from GAUSS to R (as an econometrician) was because of the existence of the library LOCFIT for local polynomial regression. While doing some checking between my former `GAUSS code' and my new `R code', I came to realize LOCFIT is not quite doing what I want. I wrote the following example script:

Dear, I am doing some statistics analysis using R software. I am currently trying to implement your library locfit. I am using Win NT and R1.1.1 version obtained on the following Webmaster : http://cm.bell-labs.com/cm/ms/departments/sia/project/locfit/index.html When trying to run it, the following message appears: ********** Error in .C("guessnv", nvm = integer(1), ncm =

I am trying to reproduce Figure 10.5 of Loader's book: Local Regression and Likelihood. The code provided in the book does not seem to work. I have managed (a while ago) to get the accompanied R-code for the figures in the book (file called lffigs.R) from somewhere - cannot find it on the web anymore. The code in the .R script file does not work either. Could anybody please direct me in