similar to: MASS fitdistr()

> for(i in c(1:5)) + { + print(identical(i,1)) + } [1] FALSE [1] FALSE [1] FALSE [1] FALSE [1] FALSE Why don't I get: [1] TRUE [1] FALSE [1] FALSE [1] FALSE [1] FALSE John Welsh Associate Professor Sidney Kimmel Cancer Center 10835 Altman Row San Diego, CA 92121 (858) 450-5990 ex.282 jwelsh at skcc.org

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

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

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 am trying to extract the shape and scale parameters of a wind speed distribution for different sites. I can do this in a clunky way, but I was hoping to find a way using data.table or plyr. However, when I try I am met with the following: set.seed(144) weib.dist<-rweibull(10000,shape=3,scale=8) weib.test<-data.table(cbind(1:10,weib.dist))

Why the warning messages (2:4)? > x <- rexp(1000,0.2) > fitdistr(x,"exponential",list(rate=1)) rate 0.219824219 (0.006951308) Warning messages: 1: one-diml optimization by Nelder-Mead is unreliable: use optimize in: optim(start, mylogfn, x = x, hessian = TRUE, ...) 2: NaNs produced in: dexp(x, 1/rate, log) 3: NaNs produced in: dexp(x, 1/rate, log) 4: NaNs

Prof Brian Ripley wrote: > > Even better, use the function fitdistr in package MASS... > I had a look in my MASS library (from the package VR_6.2-6) and couldn't find this function. Is there a newer version available? Thanks for any help. Jim This email message and any accompanying attachments may contain confidential information. If you are not the intended recipient, do not

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

In the docs I see: Usage fitdistr(x, densfun, start, ...) Arguments x A numeric vector. densfun Either a character string or a function returning a density evaluated at its first argument. Distributions "beta", "cauchy", "chi-squared", "exponential", "f", "gamma", "geometric", "log-normal", "lognormal",

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:

For a lark, I experimented a bit with the data from Ted Byers' recent postings. The result of fitdistr() seemed sensible, but I was bothered by the warnings about NaNs that arose. Warnings always make me nervous. Explicitly this is what I did: TXT <- "0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

OK, I am now at the point where I can use fitdistr to obtain a fit of one of the standard distributions to mydata. It is quite remarkable how different the parameters are for different samples through from the same system. Clearly the system itself is not stationary. Anyway, question 1: I require a visual perspective of the fit I get. I can use hist.scott to get a hisogram (and just have to

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)

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)

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