similar to: Multivariate testing or Taguchi Testing on Ruby?

Dear R Users, If it is possible, i would like to learn whether a R package that can be used for Taguchi design is available. Sincerely -- Ýbrahim Mutlay [[alternative HTML version deleted]]

Hi, I am using the mAr package to calibrate an Multivariate model (size 3, order 12). I am trying to do the two following things: 1. I would like to calibrate the model using not a single time series, but several of them: each time series should be seen as one "independent" realisation of the mAr process; for instance this happens when you have a time series with lacking data

Hi, I am working on a multivariate linear regression of the form y = Ax. I am seeing a great dispersion of y w.r.t x. For example, the correlations between y and x are very small, even after using some typical transformations like log, power. I tried with simple linear regression, robust regression and ace and avas package in R (or splus). I didn't see an improvement in the fit and

Dear Community, For my masters thesis I need to perform a multivariate granger causality test. I have found a code for bivariate testing on this page (http://www.econ.uiuc.edu/~econ472/granger.R.txt), which I think would not be useful for the multivariate case. Does anybody know a code for a multivariate granger causality test. Thank you in advance. Best Regards -- View this message in context:

Hello, I have a question about multivariate Shapiro-Wilks test. I tried to analyze if the data I have are multivariate normal, or how far they are from being multivariate normal. However, any time I did >mshapiro.test(mydata) I get the message: Error in solve.default(R %*% t(R), tol = 1e-18) : system is computationally singular: reciprocal condition number = 5.38814e-021 I tried

Hi, I am doing my PhD and I usually use SPSS however now I need to do some multivariate nonparametric tests but SPSS don?t work with this. Recently I was aware of R and I saw that is possible using the MNM pack to perform multivariate nonparametric tests. I am learning step by step how to work in R meanwhile I need to perform the multivariate nonparametric tests for my PhD and I have no idea

Dear R-users I've simulated a longitudinal multivariate normal data set from which I've simulated missing-patterns such as MCAR MAR and a simple kind of non-MAR. I've imputated the values so I now have 'complete' data sets. I'm trying to perform a T2-test as done in the multivariate case under th enormal assumption. Is there something I've to think about when performing

My stat textbook tells me that using Shapiro-Wilk test for each variable one by one is not equal to a test for multivariate normality as a whole. Does R have a function of testing for multivariate normality? Thanks. Hongsheng (Hank) Liao, Ph.D. Lab Manager Center for Quantitative Fisheries Ecology 800 West 46th Street Old Dominion University Norfolk, Virginia 23508 Phone:757.683.4571

Hello, Could someone help me to explain the VERY big difference in applying two tests on multivariate normality: library(mvnormtest) data(EuStockMarkets) mshapiro.test(t(EuStockMarkets[15:29,1:4])) Shapiro-Wilk normality test data: Z W = 0.8161, p-value = 0.005955 and library(energy) mvnorm.etest( EuStockMarkets[15:29,1:4] ) Energy test of multivariate normality:

Hello, I am wanting to use MRF to do multivariate regression. We are testing whether acoustic indices can predict structure (relative abundances) of vocalising avian community in UK and Ecuador. There are 26 acoustic indices, 65 UK species and 95 Ecuadorian species. I want to build a model for each ecozone (UK/ EC) using all species (relative abundance) as response matrix, and acoustic indices as

Dear WizaRds, I am sorry to bother you with a newbie question, but although I tried to solve my problem using the various .pdf files (Introduction, help pages etc.), I have come to a complete stop. Please be so kind as to guide me a little bit along my way of exploring multivariate analysis in R. I want to test wether the means-vector mu1 of X, consisting of the means per column of that matrix

Full_Name: Yves Rosseel Version: 2.2.1 OS: Submission from: (NULL) (157.193.116.152) The code below sketches a possible implementation of a function 'mlh.mlm' which I think would be a good complement to the 'anova.mlm' function in the stats package. It tests a single linear hypothesis of the form H_0: LBT'= 0 where B is the matrix of regression coefficients; L is a matrix

Hi all, How can a multivariate Poisson time series be modeled? Aspects of glm, forecast, dse and dynlm seem relevant but not quite complete--but hopefully what I am missing is how to assemble them effectively. What I am looking to do is model my dependent variable y_t as a Poisson family function of lags of several independent variables and lags of y_t. I would like to include all lags up

-----Original Message----- From: Vayssi?res, Marc Sent: Tuesday, June 20, 2006 9:35 AM To: 'r-help-bounces at stat.math.ethz.ch' Subject: RE: [R] multivariate splits Glen De'ath's package for R is on cran! It is called mvpart, see: http://cran.cnr.berkeley.edu/doc/packages/mvpart.pdf Cheers, Marc Vayssi?res -----Original Message----- From: r-help-bounces at stat.math.ethz.ch

Dear R Helpers, I have searched for any R package or code for simulating multivariate fractional Brownian motion (mFBM) or multivariate fractional Gaussian noise (mFGN) when a covariance matrix are given. Unfortunately, I could not find such a package or code. Can you suggest any solution for multivariate FBM and FGN simulation? Thank you for your help. Best Regards, Ryan ----- Wonsang You

Hi! I know that there is function in fBasics package for univariate Jarque-Bera test and a funtion for univariate Ljung-Box test in stats package. But I am wondering if there is a function somewhere to do the tests for multivariate time series? Thanks, John [[alternative HTML version deleted]]

Generic question... I am familiar with generic power calculations in R, however a lot of the data I primarily work with is multivariate. Is there any package/function that you would recommend to conduct such power analysis? Any recommendations would be appreciated. Thank you for your time, Charles [[alternative HTML version deleted]]

Hello folks, many multivariate anayses (e.g., structural equation modeling) require multivariate normal distributions. Real data, however, most often significantly depart from the multinormal distribution. Some researchers (e.g., Yuan et al., 2000) have proposed a multivariate transformation of the variables. Can you tell me, if and how such a transformation can be handeled in R? Thanks in

Hi, there. I have two questions about the diagnostics in multivarite statistics. 1. Is there any diagnostics tool to check if a multivariate sample is from multivariate normal distribution? If there is one, is there any function doing it in R? 2. Is there any function of testing if two multivariate distribution are same, i.e. the multivariate extension of Kolomogrov-Smirnov test? Thanks for

Hello, I would like to get the likelihood ratio and score tests for specific variables in a multivariate coxph model. The default is Wald, so the tests for each separate variable is based on Wald's test. I have the other tests for the full model but I don't know how to get them for each variable. Any idea? David Biau. [[alternative HTML version deleted]]