similar to: fitdistr() Error

In glm() you can use the summary() function to recover the shape parameter (the reciprocal of the dispersion parameter). How do you recover the scale parameter? Also, in the given example, how I estimate and save the geometric mean of the predicted values? For a simple model you can use fitted() or predicted() functions. I will appreciate any help. ? ? ? #Call required R packages require(plyr)?

Is there a way of executing SAS codes in R environment?   Peter Maclean Department of Economics UDSM [[alternative HTML version deleted]]

Chaps, Perhaps this question is a little basic for this list but I''m not really sure of the simplest method or best tool for the job. I''ve created some images with `dd=/dev/zero ....` and I''m using them for the domUs now. Some of them have been running for a few months with no probs. Trouble is that I''d like to create a separate partition within the domU.

Thanks to Thomas Lumley for the very quick fix of the NextMethod(.Generic) bug. The patch enclosed in his message to r-help fixed that problem nicely. But..., I've got another one. x <- 1:4 attr(x,"foo") <- "bar" attributes(x < 4) returns NULL. The "foo" attribute has been lost in the "x < 4" operation. The blue book says that the

Morning chaps, From my understanding the puppet master must have a hostname of "puppet". Is this correct? I''d like to be able to call this box whatever I like. I think that I can do that within /etc/puppet/puppet.conf. -- John Maclean MSc (DIC) Enterprise Linux Systems Engineer -- You received this message because you are subscribed to the Google Groups "Puppet

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

Hi all, I'm using the function "fitdistr" (library MASS) to fit a distribution to given data. What I have to do further, is getting the log-Likelihood-Value from this estimation. Is there any simple possibility to realize it? Regards, Carsten

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") :

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

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, 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:

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",

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

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

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

Hi, I have a variable X classified in a lot of groups and I need to run the [fitdistr] funtion for each group. I tried with the [by] or the [tapply] funtions because my data is organize in two columns (variable and the groups), but neither of these command work. If somebody have a tip to help me up I really appreciate it. thanks, [[alternative HTML version deleted]]

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

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

Hello everyone, This is Kangmin. I am trying to produce shape and scale of my wind data. My data is based on wind speed frequency with 1km/hr increment. data is described below. Windspeed (km/h) Frequency 1 351 2 147 3 317 4 378 5 527 6 667 7 865 8 970 9 987 10 907 11 905 12 642 13 1000 14 983 15 847 16 842 17 757 18 698 19 632 20 626 21 599 22 529 23 325 24 391

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