similar to: NonParametric Anova

i am trying to fit a survival regression model (cox model or parametric model) in R by including the covariate effects as a function m(x) instead of just beta*x. is it possible to fit such a model? can someone recommend some reference? I searched but only found a package called addreg where the hazard is actually modeled additively. That is not what i want. [[alternative HTML version deleted]]

Dear all, I have a bivariate dataset from a preliminary study. I want to do two things: (1) estimate the probability density of this bivariate distribution using some nonparametric method (kernel, spline etc); (2) sample a big dataset from this bivariate distribution for a simulation study. Is there any good method or package I can use in R for my work? I don?t want parametric models like

Dear Rusers, As we all know , there are many methods to do multiple comparison in the parametric statistical analysis, But i can't find some in nonparametric statistical analysis. Could anybody give some suggestions? [[alternative HTML version deleted]]

My interpretation of the relation between 1-way ANOVA and Wilcoxon's test (wilcox.test() in R) is the following. 1-way ANOVA is to test if two or multiple distributions are the same, assuming all the distributions are normal and have equal variances. Wilcoxon's test is to test two distributions are the same without assuming what their distributions are. In this sense, I'm wondering

Dear all, Does R or S-plus or any of their packages provide Non-parametric "Run test" (which tests whether a sequence of numbers might be random or not)? If yes, i'd like a numerical illustration of this test. Any response / help / comment / suggestion will be greatly appreciated. Thanks in advance. ------------------------------- Mohammad Ehsanul Karim <wildscop at

I've been looking for ways to calculate a large number (100) of non-crossing Nonparametric quantile regressions on large populations (1000+). Can the quantreg package in R ensure the non-crossing property? If not, do you know any alternative? Thank you, Paulbegc -- View this message in context:

Well fellow R users, I throw myself on your mercy. Help me, the unworthy, satisfy my employer, the ungrateful. My feeble ramblings follow... I've searched R-Help, the R Website and done a GOOGLE without success for a one way ANOVA procedure to analyse data that are both non-normal in nature and which exhibit unequal variances and unequal sample sizes across the 4 treatment levels. My

hey list! having a slightly odd time issue on one host... can I get some help with this? This is the current time from a working system: Sun Apr 17 00:28:18 EDT 2011 However from the problem system this is the time: Sat Apr 16 20:30:01 EDT 2011 I have set the time zone as such: lrwxrwxrwx 1 root root 23 Apr 16 19:41 /etc/localtime -> /usr/share/zoneinfo/EST But when I run ntpdate

Hello all, I'm a relatively new user of R, having mostly used it only for plotting so far. I'm also not very familiar with regression methods, hence forgive my greenness on the topic. What I want to do in R is multivariate nonparametric regression, with a slight hitch. From my experimental data I have a multitude of samples whose values approximate a function `f' that is defined

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())

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())

Dear r-users, Any such a way that we can compute SPI using kernel function (nonparametric approach) without assuming any parametric distributions? Any existing package for above method using R? Thank you for your help. Fayyad [[alternative HTML version deleted]]

Dear R Christoph Lehmann asked about this recently- as seen at http://finzi.psych.upenn.edu/R/Rhelp02a/archive/53191.html but the reply was not detailed. Did Christoph get a solution to this? Can anyone point me toward how to do repeated measures comparison using the the friedman test or other non-parametric test? I am trying to do something similar. Any example code would be useful.

Hello, I tried to post this earlier, but it seems that it did not appear on the list. If you've rec'd 2 m I'm trying to calculate non-parametric probabilities using the np package and having some difficulties. OS is Windows, R version 2.11.1 Here is what I've done so far. library(np) veg <- data.frame(factor(Physiogomy), meanAnnualDepthAve, TP) attach(veg) : for

Get some question about the function "gam". Suppose I have a semiparametric model, Y~x1+x2+s(z1). Using "gam", how could I get the estimates for the parametric part and nonparametric part respectively? And another question: we could find the coefficients for both parametric term and nonparametric term, what do these coefficients for the nonparametric term stand for, the

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I am new to R. I'm using the function GAM and wanted to get standard errors and p-values for the parametric terms (I fitted a semi-parametric models). Using the function anova() on the object from GAM, I only get p-values for the nonparametric terms. Does anyone know if and how to get standard errors for the parametric terms? Thanks. Jean G. Orelien

Hi, I have couple of questions that those who design unconventional passes would be interested in. 1. How to move a virtual register data to another new virtual register? It seems like that there is no LLVM instruction similar to mov machine instruction. Arithmetic or logical operators could be used for integer variables but what about pointer variables? 2. What is

Hi, The source attached at the bottom is a testcase which causes a back-end error in LLVM 2.4. These types of assembly routines are mainly used in OS kernels. I checked that GCC 4.3 works for this routine. The error messsage is ... Couldn't allocate output reg for constraint 'A'! I just need help or comments so that I could analyze and fix this bug. My

Hi All, What do you consider to be the best book(reference) on nonparametric regression? I am currently reading the book of Kunio Takezawa(2006): "Introduction to nonparametric regression". Is the book of Hardle(1990): "Applied nonparametric regression" better? or maybe another book? This is off topic, but most of the books is using R or S-plus. Thanks Hennie