similar to: 'fitdistr' and two views of the same data?

Hello, I am trying to run a logistic regression with random effects on proportional data in glmmBUGS. I am a newcomer to this package, and wondered if anyone could help me specify the model correctly. I am trying to specify the response variable, /yseed/, as # of successes out of total observations... but I suspect that given the error below, that is not correct. Also, Newsect should be a

I am using the Ben bolker's R package "bbmle" to estimate the parameters of a binomial mixture distribution via Maximum Likelihood Method. For some data sets, I got the following warning messages: *Warning: optimization did not converge (code 1: ) There were 50 or more warnings (use warnings() to see the first 50)* Also, warnings() results the following: *In 0:(n - x) : numerical

Hey all, I''m rather new to Ruby and Rails (and not great with SQL), but I''m developing a ride sharing app and would like to be able to sort on something I don''t have stored. I have users, events, and rides, each of which has a zip code. Events have_many rides, and rides belong_to events. When an event is selected, I''d like to be able to show a list of

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

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

Hi, Well, i need some help, practical and theoretical. I am wondering why the fitdistplus (mle function) is returning an error for this code: [code] x1 <- c(100,200,140,98,97,56,42,10,2,2,1,4,3,2,12,3,1,1,1,1,0,0); plotdist(x1); descdist(x1, boot =1000); y<- sum(x1); d= as.vector(length(x1)); for(i in 1:length(x1)){ d[i] = x1[i]/y; } fitdist(d, "beta") [/code] Error:

Hi, I am trying fit certain data into Beta distribution. I get the error saying "Error in fitdist(discrete_random_variable_c, "beta", start = NULL, fix.arg = NULL) : the function mle failed to estimate the parameters, with the error code 100" Below is the sorted data that I am trying to fit. Where am I going wrong. Thanks a lot for any help. Vinod

Hello everyone, I was trying to do some distribution fitting with a numerical field called Tolls. The sample size = 999 rows. Basically I assigned the Toll data to a new variable K by doing: k<-dtest$Toll After that, tried to fit a gamma distribution by doing: fitG<-fitdist(k, "gamma") Then the following messages showed (oh and I checked for empty rows before doing this):

>From the documentation I have found, it seems that one of the functions from package plyr, or a combination of functions like split and lapply would allow me to have a really short R script to analyze all my data (I have reduced it to a couple hundred thousand records with about half a dozen records. I get the same result from ddply and split/lapply: >

Dear Sirs, The below listed code fits a gamma and a pareto distribution to a data set danishuni. However the distributions are not appropriate to fit both tails of the data set hence a mixed distribution is required which has ben defined as "mixgampar" as shown below. library(fitdistrplus) x<- danishuni$Loss fgam<- fitdist(x,"gamma",lower=0) fpar<-

Dear R-helpers, I am trying to fit my data to a 4-parameter lognormal distribution (aka Johnson Sb dist) with fitdist function from the library(fitdistrplus). So far, I have learnt that with "mle" method it's not always possible to estimate the gamma and delta parameters even if the bounding estimates are "known"/"guessed". Therefore, I tried to fit it with the

Hi, Let say I have data by two columns A and B, and I have fit each column using the gamma distribution by 'fitdist' . I just want the result show only the shape and rate only. Eg: library(fitdistrplus) A <-c(1,2,3,4,5) B<-c(6,7,8,9,10) C <-cbind(A,B) apply(C, 2, fitdist, "gamma") Output show like this: $A Fitting of the distribution ' gamma ' by maximum

Dear Charles, Please, when you have questions about fitdistrplus, contact directly the authors of the package and not R-help. When fitting non ? standard ? distributions with fitdistrplus, you should define by yourself the density and the cumulative distribution functions, or load a package which define them. See FAQ for a general example :

Hello, I like to fit data against a negative binominal distribution x2<-c(rep(10,14),rep(9,8),rep(8,13),rep(7,11),rep(6,6),rep(5,18),rep(4,7),re p(3,21),rep(2,33),rep(1,55),rep(0,225)) f2<-fitdist(x2,"nbinom",method="mle") plot(f2) summary(f2) gofstat(f2) I receive the following result: Fitting of the distribution ' nbinom ' by maximum

Hi, I am trying to estiamte parameters for gamma distribution using mle for below data using fitdist & fitdistr functions which are from "fitdistrplus" & "MASS"packages . I am getting errors for both functions. Can someone please let me know how to overcome this issue?? data y1<- c(256656, 76376, 6467673, 46446, 3400, 3100, 5760, 4562, 8000, 512, 4545, 4562,

Capture the results of the apply command into an object and then work with that. Here is one way to do it: > res <- apply(C, 2, fitdist, "gamma") > out <- c( res$A$estimate["shape"], res$B$estimate["shape"], res$A$estimate["rate"], res$B$estimate["rate"]) > names(out) <- c("A shape","B shape","A

Hi all, I'm currently working on the fitdistrplus package (that basically fit distributions). There is something I do not understand about the generic function summary. In the current version on CRAN, there is no NAMESPACE saying S3method(summary, fitdist) . However if we use summary on an object send by fitdist function it works fine... According to R-lang, we have " The most

Hi, I am trying to fit a Johnson SB distribution using fitdist function in fitdistrplus Library. I have defined the Johnson SB distribution from ( http://www.ntrand.com/johnson-sb-distribution/) . But it gives me the follwing errors. Any help would be appreciated #xi = xi #lambda =l #delta =d #gamma = g djohn = function(x,xi,l,d,g) (d/(l*sqrt(2*pi)*((x-xi)/l)*(1-((x-xi)/l))))*exp[-0.5*(g +

Hi, sorry for repeating the question but this is kind of important to me and i don't know whom should i ask. So as noted before when I do a parameter fit to the beta distr i get: fitdist(vectNorm,"beta"); Fitting of the distribution ' beta ' by maximum likelihood Parameters: estimate Std. Error shape1 2.148779 0.1458042 shape2 810.067515 61.8608126 Warning

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