similar to: automathic bandwidth for multivariate local regression

Hello to everybody, Somebody know how I can apply the instruction (regband) of the package (locfit) to a multivariate covariate. In the instructions states that the formula has to have only one predictor. How can I use that when I have an unknown function with two predictors, m(X,Z)? Is there any other way to get a bivariate bandwidth in a local regression polynomial? I'll appreciate any

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)

Hello, I want to create a matrix of N random numbers with a uniform distributions. Later, I want to repeat T times each row of this matrix. For this I do the following loop: N<-45 T<-10 n<-N*T a<-matrix(runif(N,min=-1,max=1),nr=N) mymat<-matrix(rep(NA,n),nr=n,nc=1) for(i in i:N){ b<-rep(a[i,],T) mymat[i,]<-b } Mi problem is that with this loop I can see the output of the

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). My program is the following: library(locfit)

Hello, I want to create two random variables (x1,x2) both with uniform distribution bounded by (-1) and (1) that has a correlation of 0.6 between them. Does somebody know how I can do it? For normal random variables I known how to implement it with the rmvnorm command but I don't know how to do it with variables uniformly distributed. Thanks a lot. Alexandra [[alternative HTML

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-devel, I'm working on Prof. Loader's new version of locfit to try to get it pass R CMD check. I'm almost there, but I have a problem with some Rd files that I hope some one can help me resolve. Here's an example: In the package there's a function called locfit.censor(). This function can be used in a few different ways: locfit.censor(x, y, cens, ...)

Hello, I am trying to estimate a multivariate regression of Y on X with regression splines. Y is (nx1), and X is (nxd), with d>1. I assume the data is generated by some unknown regression function f(X), as in Y = f(X) + u, where u is some well-behaved regression error. I want to estimate f(X) via regression splines (tensor product splines). Then, I want to get the predicted values for some new

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

The version of locfit on the web site mentioned apparently has been revised by Prof. Loader, and is newer than the CRAN version that I have been maintaining. If Prof. Loader is OK with it, I will take a look and see if I can get the new version into CRAN-conforming form and upload to CRAN. Meanwhile, make sure you're using the package from Prof. Loader's web page, instead of the one on

Hello!! At first thank you all for your suggestions and your help. But I would like to get another group of datas from the density estimation. I don't know if these information are provided by locfit or I should use an other function like plot(). Description: Each number between 1 and 100 (only integer) for example should have only one density value. But I also would like to have the density

Apologies for the coming to this late... 1. By now I hope Somkiat has realized that R-bugs is not the place to report problems in contributed packages. Please direct such reports to the package maintainer. 2. This is really user error. predict() expect the newdata to be a data frame containing variables with the same names as those used in the fitting process. E.g., you fitted the model with

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

Hello!!! Thank you all for your suggestion on my last question about locfit. Now I have another question: I would like to change the evalution structure ev in locfit() to a vector/matrix. I created a vector and a matrix: > vec <- mat.or.vec(101, 1) > vec <- c(0:100) > mat <- matrix(data = vec, nrow = 101, ncol = 1) and I tried to change the ev parameter: > fit <-

I have a dataset of pregnancy values for multiple years (and ages, not included) with missing years. I would like to use local polynomial regression to smooth the values and estimate for the missing years. I would also like to use GCV to justify the smoothing parameter selection. When using locfit() with lp() I found that the gcvplot function does not work as it is looking for an alpha value to

Full_Name: Somkiat Apipattanavis Version: 2.1.1 OS: Windows Submission from: (NULL) (128.138.44.123) Bug found in predict.locfit for density estimation # Example of bug found in prdict.locfit (Locfit) library('locfit') # generate data y =c(4281,2497,4346,5588,5593,3474,4291,2542,5195,4056, 3114,2864,4904,7625,3377,4001,4999,7191,8062,5668) x1=c( 0.258729, 1.460156, 0.192323,

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

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

Hello! I am having a problem understanding what the weights option in the locfit command of the locfit package is doing. I have written a sample program which illustrates the issue (below). The example involves using bootstrap however, that is not my main goal but it illustrates where my problem lies. As you know, to compute a bootstrap estimate of a particular quantity using a sample size of

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