similar to: Have another apparent version skew

I am working with a model that I have to estimate a nonparametric function. The model is partial linear i.e. Y=X$\beta$ + f(z) + $\epsilon$ I am using the ' double residual methods' Robinson (1988) Speckman (1988) where I estimate a nonparametric function for each of the parametric variables in terms of the nonparametric one i.e. X[,i]=g(Z)+ u this is done because I need the $E(

Hello, I am a newbie to R and the subject of density estimation in two dimensions or more. I would like to have some advice concerning a comparison between the R packages for density estimation in bivariate or higher order problems; I mean explicitly the packages: 1) ash 2) KernSmooth 3) locfit 4) sm. My specific problem now is having a set of numerical pairs (x_i, y_i), arising from a

Hi, I'm using R 1001 for Windows NT and the sm library. I'm trying to create plots for my data set like Bowman and Azzalini have in Figure 1.8 (p. 9) of their book for my data (i.e. a contour plot for each group in my data set and its all plotted on 1 plot). The problem I'm having is that R is not drawing closed contour lines for each group. Sometimes it does; other times it

Full_Name: Ed Borasky Version: 1.8.1 OS: Windows XP Professional Submission from: (NULL) (208.252.96.195) R 1.8.1 seems to be running into a memory allocation problem in the "aggregate" function. I have a rather large dataset (14 columns by 223,000 rows -- almost 40 megabytes) and a script that performs some processing on it. The system is a 768 MB Pentium 4. Here's the console

Dear R experts, density estimation on a 2 dimensional bounded domain --------------------------------------------------------------------- I am currently trying to estimate the probability density (PD) of cancers within the breast using the sm library with the routine sm.density Of course a practical PD must be limited by the curve of the breast outline. I don't have a clue after perusing

Hello: I have been using sm.binomial() in the Bowman and Azzalini's sm package to smooth and plot estimated probabilities as a function of a covariate. I am concerned about my choice of bandwidth, and I was hoping there was another method available in some other package, perhaps with an automatic choice of smoothing parameter. Does anyone know of one? Thanks in advance. Tom Richards

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Caio Lucidius > Naberezny Azevedo > Sent: 01 September 2005 12:09 > To: Help mailing list - R > Subject: [R] Multivariate Skew Normal distribution > > > Hi all, > > Could anyone tell me if there is any package (or function)

Hi R-users,  I have a data from multi skew t and would like to transform each of the data to uniform data.  I tried using 'pmst' but only got one output:   > rr1 <- as.vector(r1);rr1  [1]  0.7207582  5.2250906  1.7422237  0.5677233  0.7473555 -0.6020626 -2.1947872 -1.1128313 -0.6587316 -1.1409261     > pmst(rr1, xi=rep(0,10), Omega=diag(10), alpha=rep(1,10), df=5) [1] 3.676525e-09

hello users of the SN package, i thought i post here some useful help on R code on the 4 moments for the skew t sampling gives seldom good results for skewness and kurtosis, so one really needs the analytical results, it took me some time to get it from the article Azzalini, A. & Capitanio, A. (2003), Distributions generated by perturbation of symmetry with emphasis on a multivariate

The sm package (by Adrian Bowman and Adelchi Azzalini) implements a variety of nonparametric smoothing techniques, centred on nonparametric regression for one or two covariates and density estimation for up to three variables. A new version of the package is now available on CRAN. In an earlier unannounced version (2.1), a variety of methods of bandwidth selection were added, with default

The sm package (by Adrian Bowman and Adelchi Azzalini) implements a variety of nonparametric smoothing techniques, centred on nonparametric regression for one or two covariates and density estimation for up to three variables. A new version of the package is now available on CRAN. In an earlier unannounced version (2.1), a variety of methods of bandwidth selection were added, with default

Hello everybody, I need your help about the package SN and the skew student distribution. Il will be very grateful if I have the solution. I construct a stochastic model with a white noise not gaussian but following a skew student distribution. I fit the noise on monthly data to obtain the four parameters. The question is : how to annualize the parameters to use my model for simulate daily data

Has Bowman and Azzalini's sm library been ported to R yet (goes with Appied smoothing techniques for data analysis book)? I had a quick go but got tied up at a silly stage of ignorance caused I think (?hope) because I have never seriously used S+ at all. Rather than waste time, perhaps some kind soul has already done it. \John

Hi all, I was looking for a non parametric survival analysis and I came up with the following sample from the web. However, I could not run it. Which library or function does "sm.regression" require? x <- runif(100,-2, 2) y <- x^2 + rnorm(50) sm.regression(x, y, h=0.5) Error: could not find function "sm.regression" Thanks Val [[alternative HTML version deleted]]

# Your mailer is set to "none" (default on Windows), # hence we cannot send the bug report directly from R. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs@r-project.org # ###################################################### Today I have installed R 1.02.1 on my MSW-95 laptop; it essentially worked, but thre are two

Hi There I have a lm object with 4 parameters and I want to test wether 2 parameters are equal using a Wald test (basically b1=b2 or b1-b2 =0). In the help file from R it says that under ANOVA the optional arguments " Terms" or "L" test whether a linear combination is equal to 0. I tried; >anova(m1, Terms = Beta1-Beta2=0) but I get the error: Object " Beta1"

Hi. I'm trying to take a data set with two independent and one dependent variable and enter a x,y value to predict the dependent with a nonparametric technique. I've been using interpp in the akima package, (windows xp, R 2.4.1), but get values that are orders of magnitude off when the predictors are slightly out of the range of the data set. Can you recommend a function for me?

Dear R helpers, I need to find out maximized log likelihoods, parameters estimates and standard errors (in parentheses) of r largest-order statistics model, with different values of r by using the function rlarg.fit. I want to specify required number of order statistics to the model. I attached my data file with this mail.please help me. Ruposh --- r-help-request at stat.math.ethz.ch wrote:

Hello please note that the code at https://stat.ethz.ch/pipermail/r-help/2006-August/110892.html to compute indices of skewness and kurtosis for the skew-t distribution is not correct. It has been kindly pointed out that i made some error in this code, which was a bit too quickly copied from the paper. The 'sn' package already contains a facility for computing the cumulants, namely

Dear R-Listers, I have spatial data on an equidistant rectangular grid, similar to topographic data. I know that there are quite a few R-packages or base functions that provide nice iso-contours plot, but I don't want a plot, just the smoothed isocontour line of ONE level (e.g. 10 mm). Data sets are large, so it would be preferable if the availability of regular grid data could be exploited,