similar to: test for multivariate normality?

w.age.female.2004 <- nls(WEIGHT ~ (alpha*TOTAL^beta)/454, start=list(alpha=1, beta=3), data=spottedseatrout2004.female.data) I am trying to fit above model to length-weight data of a fish species (spotted seatrout) by year (1999-2006). The convergence occurred for all the years except 2002 and 2004. In these two year, R shows the error called

Attached is a histogram chart with a break on y-axis which my friend made for me using phot shop. Do anyone know how to make such a break using R? Thanks in advance. (See attached file: 2007 age distribution.doc) 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

Where can I download Bhat package? I need to use plkhci function in this package, which estimates confidence interval using likelihood ratio. Thanks. Hongsheng (Hank) Liao, PhD. Lab Manager Center for Quantitative Fisheries Ecology Old Dominion University 757-683-4571 [[alternative HTML version deleted]]

I am trying to fit a logistic model to my 10 year data (1999-2008) by year. Codes like below: Year <- c(1999: 2008) for(y in 1:length(year)) { file.input <- paste("C:\\", year[y], "\\data.csv", sep="") table <- read.csv(file=fileinput, header=TRUE, as.is=TRUE, na.strings=c("")) initial <- getInitial(percent ~ SSlogis(age, Asym,

Dear all, I want to save the p-value from mshapiro.test(mvnormtest). But mshapiro.test(mvnormtest) gives a list with class "htest" containing statistic, p.value, method and data.name as a whole. How do I save only p-value from the result? Thanks a lot!

Dear all, I have a multivariate dataset containing 100,000 or more points. I want find the p-value for the dataset of points coming from a particular multivariate normal distribution With mean vector u Covariance matrix s2 So H0: points ~ MVN( u, s2) H1: points not ~ MVN( u, s2) How do I find the p-value in R? To me this is a likelihood ratio test problem. In H0 the parameters are

is there any function under R that allows me to test the normality of my 92 sumples? -- View this message in context: http://www.nabble.com/multinormality-tp17717230p17717230.html Sent from the R help mailing list archive at Nabble.com.

Dear all, When I print out princomp's loading outputs, there is alwasy a section for "SS loading", "Proportional Var" and "Cumulative Var". Anybody can tell what they are for? Or anyone can direct me to some reference to read about? Any help will be highly appricated. Hongsheng [[alternative HTML version deleted]]

Good Night I made different test to check normality and multinormality in my dataset, but I don´t know which test is better. To verify univariate normality I checked: shapiro.test, cvm.test, ad.test, lillie.test, sf.test or jaque.bera.test and To verify multivariate normal distribution I use mardia, mvShapiro.Test, mvsf, mshapiro.test, mvnorm.e. I have a dataset with almost 1000 data and 9

Dear All,   I often have to work with certain models in which I try to "reproduce" a distribution the best I can with very little known information avaible. Is there a package or function in R that could best reproduce a probability distribution using only the mean, median and SD values availble without knowing the actual distribution type to begin with and/or the covariance matrix (for

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

x <- iris$Sepal.Length[1:50]/iris$Sepal.Width[1:50] y <- iris$Petal.Length[1:50]/iris$Petal.Width[1:50] I want to check whether (x,y) follows a bivariate normal distribution or not, using density plot or scatter plot. Is it possible to plot a bivariate density in R. I cant find any. Arindam Fadikar M.Stat Indian Statistical Institute. New Delhi, India [[alternative HTML version

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:

Hi, I have a question about the p-value of mshapiro test. I simulated data from bivariate normal 1000 times and used mshapiro test to see how many times the test would reject the null hypothesis when the p-value is 0.05. The answer should be around 50 since the p-value is 0.05. But I got a much higher value. Here is the R code I used and the result.

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

Dear all, I got this error message > library(dprep) > mardia(Savg) Error in cov(data) : 'x' is empty But with the same data, I got > library(mvnormtest) > mshapiro.test(Savg) Shapiro-Wilk normality test data: Z W = 0.9411, p-value = 0.6739 What does the error message "Error in cov(data) : 'x' is empty" mean? Thanks a lot! Jiao

Hi all, I have a huge data set. All I want to do is to change the column names of the it. So if I use read.table, I can read the data in and change colnames and then write back, such as, t <- read.table("a.txt", header = T, sep = "\t") colnames(t) colnames(t) <- c("....) # new column names write.table(t, "a.txt", quote = F, sep = "\t",

On Thu, Sep 6, 2012 at 10:56 AM, Michael LIAO <michael.hliao at gmail.com>wrote: > On Thu, Sep 6, 2012 at 10:02 AM, Reed Kotler <rkotler at mips.com> wrote: > > Here is the problem explained more. > > > > Normally there is a 64 bit register that is the result of certain > multiply > > and divide instructions. > > It's really 2 32 bit registers.

Hola! Estoy teniendo un problema para testar la normalidad y la homogeneidad de varianzas para mi modelo de manova Es este mi modelo: m1<-manova(cbind(pred,fit,oniv)~tratamento/parcela+bloco,data.vegetacao) Aparte de tener tres variables respuestas (predador, fitófago, omnívoro), también es un diseño anidado. Alguien sabría responder esto? Gracias! Carol [[alternative HTML version

+llvm-dev Yes. The question then becomes, does LLVM handle the case where the cast of the value 0 to a non-void* pointer? Think of this case: int *ptr = (int*)0; based on a strict reading of the spec, ptr itself technically is not the null pointer constant. If ptr points to an object in the local address space in OpenCL, or any address space where 0 is a valid address and memory exists, does