similar to: package 'np' and point estimation with multiple predictors

Hi, I am looking for some help concerning the npudens function in the np package. I am trying to find a kernel density function of a multivariate dataset and the density evaluated at each of the 176 points. I have 2 continuous and 3 ordered discrete variables. My sample size is 176. So edata is a 176x(2+3) data frame, while tdat is a 1x(2+3) vector. bw_cx[i,] is a 1x (2+3) vector

Hi List, I'm trying to get a density estimate for a point of interest from an npudens object created for a sample of points. I'm working with 4 variables in total (3 continuous and 1 unordered discrete - the discrete variable is the character column in training.csv). When I try to evaluate the density for a point that was not used in the training dataset, and when I extract the fitted

Hi all, I want to use the npudens() function in the np package (multivariate kernel density estimation), but was confused by the several functions in the following codes,expand.grid(),array(),image() and npudensbw(). This confusion will only be generated in >=3 dimensions. I marked the four places with confusion1-4. I think there should be some kind of correspondence in those four

Hi - I'm just geting started with R, specifically needing to plot some 3D joint distribution functions estimated from data. Happily, the "np" package includes example code which gets most of the way there. The following tweak of the doc code gives me a nice cdf: library(np) library(datasets) data(faithful) f <- npudens(~eruptions+waiting,data=faithful) plot(f,cdf = TRUE,

Hi, I'd like to use a three-dimensional dataset to build a kernel density and then sample from the distribution. I already used the npudens function in the np package to estimate the density and plot it: fit<-npudens(~x+y+z) plot(fit) It takes some time but appears to work well. How can I use this to evaluate the fitted function at a certain point, e.g. (x=1, y=1, z=1)?

Dear useRs, We are pleased to announce that versions 0.50-1 of the np package and its MPI-aware counterpart, the npRmpi package, are now available on CRAN: http://cran.r-project.org/web/packages/np/index.html http://cran.r-project.org/web/packages/npRmpi/index.html In these versions we add new functionality: - new methods for multivariate mixed-data bandwidth selection for unconditional and

Dear useRs, We are pleased to announce that versions 0.50-1 of the np package and its MPI-aware counterpart, the npRmpi package, are now available on CRAN: http://cran.r-project.org/web/packages/np/index.html http://cran.r-project.org/web/packages/npRmpi/index.html In these versions we add new functionality: - new methods for multivariate mixed-data bandwidth selection for unconditional and

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.20-0). Version 0.20-0 is documented in Tristen Hayfield and Jeffrey S. Racine (2008). Nonparametric Econometrics: The np Package. Journal of Statistical Software 27(5). URL http://www.jstatsoft.org/v27/i05/ and also in a vignette (vignette("np",package="np")). There is also a FAQ

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.20-0). Version 0.20-0 is documented in Tristen Hayfield and Jeffrey S. Racine (2008). Nonparametric Econometrics: The np Package. Journal of Statistical Software 27(5). URL http://www.jstatsoft.org/v27/i05/ and also in a vignette (vignette("np",package="np")). There is also a FAQ

Dear R-users, I am fitting a kernel regression model of the form y ~ x1 + factor(x2) + factor(x3) and am using the function npregbw in the np-package to find the optimal bandwidths. My dataset is relatively large and the optimization takes quite long. When testing different specifications I have noticed that the optimal bw for x3 is always very close to zero (around 10^-12 or so). I am

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.14-1). The package is briefly described in a recent issue of Rnews (October, 2007, http://cran.r-project.org/doc/Rnews/Rnews_2007-2.pdf) for those who might be interested. A somewhat more detailed paper that describes the np package is forthcoming in the Journal of Statistical Software

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.14-1). The package is briefly described in a recent issue of Rnews (October, 2007, http://cran.r-project.org/doc/Rnews/Rnews_2007-2.pdf) for those who might be interested. A somewhat more detailed paper that describes the np package is forthcoming in the Journal of Statistical Software

I am trying to graphically represent a large set of data who's result is not strictly uniform. http://n4.nabble.com/file/n961629/egraph_rules_list_2.png The scatter plot to the left has all of the data rising in steps however I know that there are cases within my data that do not fit the dotted line. temp<-edat[edat$R1SC>0,,]

Dear all, I am using np package in order to estimate a model with Klein and Spady estimator. To estimate the model I use KS <- npindexbw (xdat=X, ydat=Y, bandwidth.compute=TRUE, method="kleinspady", optim.maxit=10^3, ckertype="epanechnikov", ckerorder=2) and to estimate beta hats standard errors I use KSi <- npindex(KS, gradients=T, boot.num=300) vcov(KSi) This is

Dear all, I would like to estimate the standard errors of Klein and Spady's estimator for that I am using: library(np) N<-100 X<-matrix(c(rnorm(N,1,1), rnorm(N,0,1)), ncol=2) BETA <-matrix(1,2,1) Z<-X%*%BETA L<-rlogis(N,location=0, scale=1) Y <-as.vector(X%*%BETA+L>=0)*1 KS <- npindexbw (xdat=X, ydat=Y, bandwidth.compute=TRUE, method="kleinspady",

Hi, I need to export a rotating plot like the one generated from the following function into a PPT slide or something that can be viewed by reviewers of a journal: library(np) library(datasets) data(faithful) f <- npudens(~eruptions+waiting,data=faithful) plot(f,view="rotate",neval=100,phi=30,main="",xtrim=-0.2) Thanks! Gabriele Zoppoli, MD Ph.D. Fellow,

Dear all, I am trying to use the np package for the estimation of a model with Klein and Spady's semiparametric estimator. When though, I include a constant term ( a column with 1s in X) then the following message appear: Multistart 1 of 3...Error in optim(c(beta, h), fn = optim.fn, gr = NULL, method = optim.method, : non-finite value supplied by optim So, how can I include a constant

Dear R users, A parallel implementation of the np package titled `npRmpi' is now available on CRAN. This package can take advantage of multiple core computing environments to reduce the run time associated with the methods contained in the np package. Kindly see the vignette for details and examples on modifying np code and running it in a parallel environment. You are requested to seek

Dear R users, A parallel implementation of the np package titled `npRmpi' is now available on CRAN. This package can take advantage of multiple core computing environments to reduce the run time associated with the methods contained in the np package. Kindly see the vignette for details and examples on modifying np code and running it in a parallel environment. You are requested to seek

Dear R users, A new package titled `np' is now available from CRAN. The package implements recently developed kernel methods that seamlessly handle the mix of continuous, unordered, and ordered factor datatypes often found in applied settings. The package also allows users to create their own nonparametric/semiparametric routines using high-level function calls (via the function npksum())