similar to: ad.test exponential distribution

Hi,I am currently doing a project in which we are to investigate the size and power of three different one sample tests over three different distributions using a number of different sample sizes and values for mu1. I have written a function and was trying to get my answer for each test into the right position in an array so the output is the power of each combination of test, distribution, sample

Hi, I am trying to figure out the observed acceptance rate and M, using generalised rejection sampling to generate a sample from the posterior distribution for p. I have been told my code doesn't work because I need to "take the log of the expression for M, evaluate it and then exponentiate the result." This is because R is unable to calculate high powers such as 545.501. As

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

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

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.

Dear experts, Helps are badly needed. I'm trying to generate a panel data with error term from N(0,1) and alpha from U(0,20).Explanatory variables are from multivariate std normal distn. Problem arised when I tried to contaminate the data in Y by adding additional term from N(50,1). I ask the computer to choose 5 random data from Y by using the command runif(5,1,50) since we have 50 data

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 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]]

Dear, R help How can I generate random numbers of the multivariate power exponential distribution. Regards, Jeremias Leão. ____________________________________________________________________________________ [[elided Yahoo spam]] [[alternative HTML version deleted]]

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 mailing list, Greetings!!! I'm doing a graphical test of suitability for the aircondit data. I actually just followed the exercise in Davison and Hinkley's book of Graphical Test for model checking. The program for testing if it comes from an exponential distribution seems to be running okay but the program for the gamma distribution distribution is running away :-). I hope

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

Hi, I'm using RF to simulate a correlated variable with GaussRF set.seed=1 GaussRF(sim.kfinegrid, grid=F, model="exponential", param=c(0,0.5,0,0.2)) However when I simulate again using the same random seed I get different results. > set.seed=1 > summary(GaussRF(sim.kfinegrid, grid=F, model="exponential", param=c(0,0.5,0,0.2))) Min. 1st Qu. Median Mean 3rd

Hi First, sorry if I get the terminology wrong, I am still quite new to the concept of using environments and workspaces. Say I have a statement in a package SIM like sim <- TYPE where the variable TYPE is initialized in the package to e.g. "exponential" (SIM::TYPE == "exponential"). Now, I want to give the user the option of specifying the variable TYPE, but to the

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