similar to: No parametric methods

Hello R experts, Is the a function to preform a Hosmer Lemshaw goodness of fit? I am running R 2.8. Thanks, AlonBen-Ari Department of Anesthesiology and CCM Univ. Pittsburgh [[alternative HTML version deleted]]

Hello I am trying to read a date and time from a file and convert them to POSIXct using strptime() the dates are stored in t which is a factor This the code I am using to illustarte > t[1] [1] 07/14/2009 13:41:00 10 Levels: 07/14/2009 13:41:00 07/14/2009 13:42:00 ... 07/15/2009 07:12:00 > a=t[1] > a [1] 07/14/2009 13:41:00 10 Levels: 07/14/2009 13:41:00 07/14/2009 13:42:00 ...

Minitab can perform a "Parametric Distribution Analysis - Arbitrary Censoring" with one of eight distributions (e.g., weibull), giving the maximum likelihood estimates of the parameters in the distribution for a given dataset. Does R have a package that provides equivalent functionality? Thanks for any advice you can offer. Tom La Bone [[alternative HTML version deleted]]

Hello R users, Is anyone familiar with an R function that converts a time expression ( POSIx for example ) to time (seconds/minutes) from epoch? I was unable to find any Best, Alon [[alternative HTML version deleted]]

Hello All, Hope you all are fine and good ... I m facing an odd problem. I am able to dial some local and Mobile Number and some are not working. I also try to remove and re create dial plans , but it's not working. I live in New Delhi and Area Code is {011} but i am bale to call the number without adding {0} by just {11}, Previously i was thinking it was PRI problem, so i called the

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 My users are complaining that to remove "Everyone" permissions from a folder's ACL they have to "Deny" all permissions. This causes a Windows warning to appear: "You have denied everyone access to New Folder. No one will be able to access New Folder and only the owner will be bale to change the permissions. Do you wish to

I was wondering if someone familiar with survival analysis can help me with the following. I would like to fit a Weibull curve, that may be dependent on a covariate, my dataframe "labdata" that has the fields "cov", "time", and "censor". Do I do the following? wieb<-survreg(Surv(labdata$time, labadata$censor)~labdata$cov,

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

Hello R, I am looking for non-parametric simulation in IRT. Is there any IRT package that does non-parametric simulation? helen L [[alternative HTML version deleted]]

Hello, I'm quite new to R and want to make a Weibull-regression with the survival package. I know how to build my "Surv"-object and how to make a standard-weibull regression with "survreg". However, I want to fit a translated or 3-parametric weibull dist to account for a failure-free time. I think I would need a new object in survreg.distributions, but I don't know how

Hi, I am trying to estimate the sample size needed for the comparison of two groups on a certain measurement, given some previous data at hand. I find that the data collected does not follow a normal distribution, so I would like to use a non-parametric option for sample size calculation. I found the pwr package but I don't think it has this option and on the internet found that

Greetings -- I would like to estimate a proportional hazard model with a weibull or lognormal baseline. I have looked at both the coxph() and survreg() functions and neither appear (to me ) to do it. Am I missing something in the docs or is there another terrific package out there that will do this. Many Thanks. Carl Mason

Hello, I am interested in parametric multi comparison tests such as Dunnett, Duncan, Tukey, Newman-Keuls, Bonferonni, Scheffe, and non-parametric tests such as Kruskal-Wallis, and Mann-Whitney U. Are there packages that include most of these tests in each category? Many packages exist for an individual test but their outputs vary in great detail (test statistics, p-values, etc.)

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Can anyone suggest a good non-parametric test, and an R implementation of the test, that allows for two or more factors? Wilcoxon signed rank allows for only one. Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC and University of Maryland School of Medicine Claude Pepper OAIC University of Maryland School of Medicine Division of

I have two data sets, each a vector of 1000 numbers, each vector representing a distribution (i.e. 1000 numbers each of which representing a frequency at one point on a scale between 1 and 1000). For similfication, here an short version with only 5 points. a <- c(8,10,8,12,4) b <- c(7,11,8,10,5) Leaving the obvious discussion about causality aside fro a moment, I would like to see how

Dear all, I am trying to find a suitable R-function for parametric proportional hazard regressions. The package survival contains the coxph() function which performs a Cox regression which leaves the base hazard unspecified, i.e. it is a semi-parametric method. The package Design contains the function pphsm() which is good for parametric proportional hazard regressions when the underlying base

Hi everybody! I'm trying to plot a parametric curve (three dimensions) using R but I didn't obtain good results. Somebody have already done something like that? Please help me! Talita Perciano Costa Leite Graduanda em Ci??ncia da Computa????o Universidade Federal de Alagoas - UFAL Departamento de Tecnologia da Informa????o - TCI Constru????o de Conhecimento por Agrupamento de Dados -

Hi all, I am currently doing a consistency analysis using an lmer model and trying to use parametric bootstrapping for the confidence intervals. My model is like this: model<-lmer(y~A+B+(1|C/D)+(1|E),binomial) where E is the individual level for consistency analysis, A-D are other fixed and random effects that I have to control for. Following Nakagawa and Scheilzeth I can work out the

Dear R experts, I have a problem that is a related to the question raised in this earlier post https://stat.ethz.ch/pipermail/r-help/2007-January/124064.html My situation is different in that I have only 2 predictors (coordinates x,y) for local regression but a number of global ("parametric") offsets that I need to consider. Essentially, I have a spatial distortion overlaid over a