similar to: Random numbers of multivariate power exponential distribution!

Hi all, Just a random shot in the dark. Does anyone have/know of a function for the CDF of a generalized error dist? -- Elliot Williams (ewilliams at ucsd.edu) Economics Department, UC San Diego -------------- next part -------------- An embedded message was scrubbed... From: Elliot Williams <ewilliams at ucsd.edu> Subject: [R] Generalized Error Distribution (Exponential Power) CDF?

Dear All, I'd like to compare exponential or power-law distributions. To do so, people are often referred to the ks.test. However, I imagine ks.test wouldn't be as powerful as a test specifically designed for a distribution type. So my question is, is there a more specific test for each of these distribution? (exponential or power-law) Thanks for your hints! E

Dear useRs, I have the following plot: pos <- c(27/44, 11/32, 8/40, 4/42, 3/40, 4/40, 2/40) tmin <- c(15.8, 12.6, 10.5, 2.4, 5.2, 8.5, 7.9) plot(tmin, pos) I would like to fit an exponential curve to it. How could I be able to do this? Thanks in advance, Rafael. ____________________________________________________________________________________ [[elided Yahoo spam]]

Hi all, I am attempting to fit, and test the goodness of fit of, a mixed exponential distribution to my dataset which consists of 15minute rainfall intensity data. FYI, the dataset spanning approx.2 years and 7 rainfall stations consists of some three hundred thousand 15min data records, of which some 30 thousand are non-zero rainfall amounts. Could anyone please tell me how i could do

Hi, I'm trying to use ad.test or ad2.test to test whether a given data set is exponential. I see that one of the function inputs is "distn", but I try "exponential" and 5 other variants, but I still get the error message: ad.test(test2, distn="exponential", fit=list(estimate = 0.167685), H=NA, sim=100) Error in ad.test(test2, distn = "exponential",

Hello! I must estimate the parameters of a exponential power density. There is the normalp package, but this works only for a shape parameter bigger than 1. But what should i do if the shape parameter is less than 1? (Sorry for my english) Thank you very much for help! -- View this message in context: http://www.nabble.com/Parameters-of-exponential-power-density-tp20774495p20774495.html Sent from

Any one know is there any package or function to generate bivariate exponential distribution? I gusee there should be three parameters, two rate parameters and one correlation parameter. I just did not find any function available on R. Any suggestion is appreciated. -- View this message in context:

Good morning, Is there anyway to do Mixed Exponential Distribution in R? I am trying to load some lag-weighted empirical survival distribution into R and run a mixed exponential on that data. Thanks, Jacob Fazekas Jacob Fazekas Assistant Actuary Auto-Owners Insurance Company 517-703-2543 fazekas.jacob@aoins.com [[alternative HTML version deleted]]

Dear R-users, I have to plot a exponential distribution like the plot in the pdf attached. I've write this code but I don't know how to draw the two lines.. Can anyone help me please? Thank you very much Pippo http://r.789695.n4.nabble.com/file/n3394476/exponential_smoothing.pdf exponential_smoothing.pdf -- View this message in context:

Dear all, I've tried to solve the Es. 12, cap 4 of "Introduction to GLM" by Annette Dobson. It's about the relationship between survival time of leukemia patients and blood cell count. I tried to fit a model with exponential distribution, first by glm (family gamma and then dispersion parameter fixed to 1) and then with survreg. They gave me the same point estimates but the

I am learning glm function, but how do you fit data using exponential distribution with glm? In the help file, under "Family Objects for Models", no ready made option seems available for the distribution as well as for other distributions satisfying GLM requirements not listed there.

Hello! I need to test the adjustment of a (Negative) Exponential Distribution to a dataset. The parameter of the distribution is unknown. What is the appropriate test to do? I've tried the ks.test, although I think this isn't the appropriate one, as I don't know the parameter. Can anybody help me? Thanks in advance, Janete -- Janete da Silva Borges janeteborges at gmx.net Ab

Given a numeric vector of observations, does R have any generic way to estimate the parameters of commonly used distributions (exponential, gamma, etc.) without numerically optimizing the likelihood function? Thanks, David _______________________________________ David R. Bickel http://davidbickel.com Research Scientist Pioneer Hi-Bred International Bioinformatics & Exploratory Research 7250

Dear All, I have fitted the exponential and gamma model to my univariate data and obtained the MLE estimates using the R package "fitdistr", now I'm trying to do model selection based on leave-one-out cross validation, are there any readily avaliable R package to do this. Thanks! [[alternative HTML version deleted]]

Is there any R function that computes the convolution of the double exponential distribution? If not, is there a good way to integrate ((q+x)^n)*exp(-2x) over x from 0 to Inf for any value of q and for any positive integer n? I need to perform the integration within a function with q and n as arguments. The function integrate() is giving me this message: "evaluation of function gave a

Hello there, I am trying to fit an exponential fit using Least squares to some data. #data x <- c(1 ,10, 20, 30, 40, 50, 60, 70, 80, 90, 100) y <- c(0.033823, 0.014779, 0.004698, 0.001584, -0.002017, -0.003436, -0.000006, -0.004626, -0.004626, -0.004626, -0.004626) sub <- data.frame(x,y) #If model is y = a*exp(-x) + b then fit <- nls(y ~ a*exp(-x) + b, data = sub, start

Dear R-users! I would like to fit exponential, Weibull and log-logistic via glm() like functions. Does anyone know a way to do this? Bellow is a bit longer description of my problem. Hm, could family() be adjusted/improved/added to allow for these distributions? SAS procedure GENMOD alows to specify deviance and variance functions to help in such cases. I have not tried that option and I do not

Dear R-users I have some datasets, all left-censoring, and I would like to fit distributions to (weibull,exponential, etc..). I read one solution using the function survreg in the survival package. i.e survreg(Surv(...)~1, dist="weibull") but it returns only the scale parameter. Does anyone know how to successfully fit the exponential, weibull etc... distributions to left-censoring

Hi all, rmvnorm()can be used to generate the random numbers from a multivariate normal distribution with specified means and covariance matrix, but i want to specify the correlation matrix instead of covariance matrix for the multivariate normal distribution. Does anybody know how to generate the random numbers from a multivariate normal distribution with specified correlation matrix? What about

I wish to generate 100 by 1 vector of x1 and x2 both are uniform distributed with covariance matrix \Sigma. Thanks, Michael [[alternative HTML version deleted]]