similar to: fitdistr for t distribution

Please guide me through to resolve the error message that I get this is what i have done. >x1<- rnorm(100,2,1) >x1fitbeta<-fitdistr(x1,"beta") Error in fitdistr(x1, "beta") : 'start' must be a named list Yes, I do understand that sometime for the distribution to converge to the given set of data, it requires initial parameters of the distribution, to

Dear R Users, I am trying to obtain a best-fit analytic distribution for a dataset with 11535459 entries. The data range in value from 1 to 300000000. I use: fitdistr(data, "gamma") to obtain mle's for the parameters. I get the following error: Error in optim(start, mylogfn, x = x, hessian = TRUE, ...) : non-finite finite-difference value [1] And the following warnings:

Hi, I'm trying fitdistr but I'm getting some errors > fitdistr(rnorm(100),"Normal") Error in fitdistr(rnorm(100), "Normal") : 'start' must be a named list > fitdistr(rnorm(100),"Normal",start=list(mean=0,sd=1)) Error in fitdistr(rnorm(100), "Normal", start = list(mean = 0, sd = 1)) : supplying pars for the Normal is not

Hello! I would like to get MLE for parameter lambda of Poisson distribution. I can use fitdistr() for this. After looking a bit into the code of this function I can see that value for lambda and its standard error is estimated via estimate <- mean(x) sds <- sqrt(estimate/n) Is this MLE? With my poor math/stat knowledge I thought that MLE for Poisson parameter is (in mixture of LaTeX

I am trying to fit the chi-squared distribution to a set of data using the fitdistr function found in the MASS4 library, the data set is called ONES3, I have loaded it using the command ONES3<-read.table("ONES3.pdf",header=TRUE,na="NA") I print out the dataset ONES3 to the screen to make sure it has loaded Then I try to fit this data using the command

Hi, I want to estimate parameters of weibull distribution. For this, I am using fitdistr() function in MASS package.But when I give fitdistr(c,"weibull") I get a Error as follows:- Error in optim(x = c(4L, 41L, 20L, 6L, 12L, 6L, 7L, 13L, 2L, 8L, 22L, : non-finite value supplied by optim Any help or suggestions are most welcomed -- View this message in context:

Hi, R users: I want to fit my data into a normal distribution by using the command "fitdistr" in "MASS". I changed my data class from "ts" to "numeric" by >class(mydata)="numeric" but after using "fitdistr", I got the result below >fitdistr(mydata,"normal") mean sd NA NA (NA) (NA) the help doc of

Dear R experts, I am trying to use the R MASS library fitdistr() to fit the following list: k21stsList<-c(0.76697,0.57642,0.75938,0.82616,0.93706,0.77377,0.58923,0.37157,0.60796,1.00070,0.97529,0.62858,0.63504,0.68697,0.61714,0.75227,1.16390,0.66702,0.83578) as follows, library(MASS) fitdistr(k21stsList, "normal") But, I get Error in fitdistr(k21stsList, "normal") :

Dear developers, There's a small bug in print.fitdistr that can cause output to be printed twice, but only if print is called explicitly: > fit<-fitdistr(rt(1000,3),"t") There were 11 warnings (use warnings() to see them) > fit m s df -0.02181723 1.00145296 3.13723878 ( 0.03865057) ( 0.03999447) ( 0.33298377) > print(fit)

Hello R community, I have two questions: The first might be one of the silliest ever posted here and I apologize if I've missed some thing very obvious. It relates to using this digest. When I subscribed to the forum, I had chosen the "digest" option that bundles all mails every day into a single digest. Now, I posted a question a while ago on the logistic regression function and

Hi R lovers! I'd like to know how to use the parameter 'start' in the function fitdistr() obviously I have to provide the initial value of the parameter to optimize except in the case of a certain set of given distribution Indeed according to the help file for fitdistr " For the following named distributions, reasonable starting values will be computed if `start'

Dear All; I tried to use fitdistr() in the MASS library to fit a mixture distribution of the 3-parameter Weibull, but the optimization failed. Looking at the source code, it seems to indicate the error occurs at if (res$convergence > 0) stop("optimization failed"). The procedures I tested are as following: >w3den <- function(x, a,b,c)

When using fitdistr() with the exponential, log-normal and beta distributions, you get the relevent rate, mean, standard deviation, shape1 and shape2 but you get a number bellow those that are in () and I was wandering what exactly those numbers represent and how they relate to the data. Many thanks Mark Miller

Sorry if it is a silly question, I haven't found documentation on this and I don't know if it is possible. library(MASS) ## for fitdistr library(msm) ## for dtnorm #prepare truncated normal distribution dtnorm0 <- function(x, mean, sd , log = FALSE) { dtnorm(x, mean, sd, 105, 135, log) } set.seed(1) #Generate normal distribution with the TRUE population mean (day 106 of the

I have the following problem: I have a vector x of data (0<x<=1 ) with a U-shaped histogram and try to fit a beta distribution using fitdistr. In fact, hist(rbeta(100,0.1,0.1)) looks a lot like my data. The equivalent to the example in the manual sometimes work: > a <- rbeta(100,0.1,0.1) > fitdistr(x=a, "beta", start=list(shape1=0.1,shape2=0.1))1) > shape1

Hello R-Users, I'm new to R so I apologize in advance for any big mistake I might be doing. I'm trying to fit a set of samples with some probabilistic curve, and I have an important question to ask; in particular I have some data, from which I calculate manually the CDF, and then I import them into R and try to fit: I have the x values (my original samples) and the y values

Dear R developers, I have encountered strange behaviour of fitdistr for gamma in recent R build i.e. 2.2.0. I have attached the code for data at the end of this mail so you can reproduce the problem. In short, I am able to run fitdistr under 2.1.0 without problems, while I get the following error under 2.2.0 (Version 2.2.0 Patched (2005-11-15 r36348)) > fitdistr(otm, "gamma") Error

Hello, I want to fit a tree parameter distribution to given data. I tried it with sample data using the "fitdistr" function. Here my workflow that didn't had any result: I started with the generalized gamma distr, which is: r*dgamma(x^r,shape,rate) The R-function is: ggamma = function (x,r,shape,rate) r*dgamma(x^r,shape,rate=rate) For the first step I assumed r = 1 and I

Hi R lovers Here is a numerical vector test > test [1] 206 53 124 112 92 77 118 75 48 176 90 74 107 126 99 84 114 147 99 114 99 84 99 99 99 99 99 104 1 159 100 53 [33] 132 82 85 106 136 99 110 82 99 99 89 107 99 68 130 99 99 110 99 95 153 93 136 51 103 95 99 72 99 50 110 37 [65] 102 104 92 90 94 99 76 81 109 91 98 96 104 104 93 99 125 89

I'm getting errors when running what seems to be a simple Weibull distribution function: This works: x <- c(23,19,37,38,40,36,172,48,113,90,54,104,90,54,157,51,77,78,144,34,29,45,16,15,37,218,170,44,121) rate <- c(.01,.02,.04,.05,.1,.2,.3,.4,.5,.8,.9) year <- c(100,50,25,20,10,5,3.3,2.5,2,1.2,1.1) library(MASS) x <- sort(x) tryCatch( f<-fitdistr(x, 'weibull'), error