similar to: Fitting Mixed Distributions in the fitdistrplus package

Displaying 20 results from an estimated 110 matches similar to: "Fitting Mixed Distributions in the fitdistrplus package"

2020 Oct 24
0
Fitting Mixed Distributions in the fitdistrplus package
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 :
2011 May 20
1
outout clarification of fitdist {fitdistrplus} output
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
2017 Feb 03
0
Announcing fitdistrplus 1.0-8
Dear useRs, We are pleased to announce you a new version of "fitdistrplus" on CRAN : https://cran.r-project.org/web/packages/fitdistrplus/index.html "fitdistrplus" is a package dedicated to help the fit of a parametric distribution to non-censored or censored data. The main new features in this release are few new topics in the FAQ vignette
2017 Feb 03
0
Announcing fitdistrplus 1.0-8
Dear useRs, We are pleased to announce you a new version of "fitdistrplus" on CRAN : https://cran.r-project.org/web/packages/fitdistrplus/index.html "fitdistrplus" is a package dedicated to help the fit of a parametric distribution to non-censored or censored data. The main new features in this release are few new topics in the FAQ vignette
2016 Jul 07
0
new version of the package fitdistrplus
We are pleased to announce your a new version of fitdistrplus ( https://cran.r-project.org/package=fitdistrplus). Among the new features of the package (https://cran.r-project.org/web/packages/fitdistrplus/NEWS), a FAQ vignette is now available ( https://cran.r-project.org/web/packages/fitdistrplus/vignettes/FAQ.html). We will be delighted to update it with new questions sent by users. Do not
2016 Jul 07
0
new version of the package fitdistrplus
We are pleased to announce your a new version of fitdistrplus ( https://cran.r-project.org/package=fitdistrplus). Among the new features of the package (https://cran.r-project.org/web/packages/fitdistrplus/NEWS), a FAQ vignette is now available ( https://cran.r-project.org/web/packages/fitdistrplus/vignettes/FAQ.html). We will be delighted to update it with new questions sent by users. Do not
2017 Nov 07
0
Fitdistrplus and Custom Probability Density
Why not define your own functions based on d? e.g. myCumDist <- function(x) { integrate(d, lower=-Inf, upper=x)$value } myQuantile <- function(x) { uniroot(f=function(y) { h(y) - x }, interval=c(-5,5)) } # limits -5,5 should be replaced by your own which might require some fiddling e.g. d <- function(x) { exp(-x^2/2)/(sqrt(2*pi)) } # just an example for you to test with; use your own
2017 Nov 07
2
Fitdistrplus and Custom Probability Density
Dear All, Apologies for not providing a reproducible example, but if I could, then I would be able to answer myself my question. Essentially, I am trying to fit a very complicated custom probability distribution to some data. Fitdistrplus does in principle everything which I need, but if require me to specify not only the density function d, but also the cumulative p and and inverse cumulative
2011 Jul 26
2
Beta distribution- help needed
Hi, Well, i need some help, practical and theoretical. I am wondering why the fitdistplus (mle function) is returning an error for this code: [code] x1 <- c(100,200,140,98,97,56,42,10,2,2,1,4,3,2,12,3,1,1,1,1,0,0); plotdist(x1); descdist(x1, boot =1000); y<- sum(x1); d= as.vector(length(x1)); for(i in 1:length(x1)){ d[i] = x1[i]/y; } fitdist(d, "beta") [/code] Error:
2012 Mar 21
2
Error in fitdist- mle failed to estimate parameters
Hi, I am trying fit certain data into Beta distribution. I get the error saying "Error in fitdist(discrete_random_variable_c, "beta", start = NULL, fix.arg = NULL) : the function mle failed to estimate the parameters, with the error code 100" Below is the sorted data that I am trying to fit. Where am I going wrong. Thanks a lot for any help. Vinod
2013 Apr 09
5
Error when using fitdist function in R
Hello everyone, I was trying to do some distribution fitting with a numerical field called Tolls. The sample size = 999 rows. Basically I assigned the Toll data to a new variable K by doing: k<-dtest$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):
2010 Jul 12
2
exercise in frustration: applying a function to subsamples
>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: >
2012 Jan 20
0
fit Johnson Sb with fitdist(method="mme")
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
2018 Jan 29
2
Result show the values of fitting gamma parameter
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: $A Fitting of the distribution ' gamma ' by maximum
2012 Feb 15
1
Parameter estimation of gamma distribution
Hi, I am trying to estiamte parameters for gamma distribution using mle for below data using fitdist & fitdistr functions which are from "fitdistrplus" & "MASS"packages . I am getting errors for both functions. Can someone please let me know how to overcome this issue?? data y1<- c(256656, 76376, 6467673, 46446, 3400, 3100, 5760, 4562, 8000, 512, 4545, 4562,
2018 Jan 29
0
Result show the values of fitting gamma parameter
Capture the results of the apply command into an object and then work with that. Here is one way to do it: > res <- apply(C, 2, fitdist, "gamma") > out <- c( res$A$estimate["shape"], res$B$estimate["shape"], res$A$estimate["rate"], res$B$estimate["rate"]) > names(out) <- c("A shape","B shape","A
2009 Sep 19
1
generic methods - in particular the summary function
Hi all, I'm currently working on the fitdistrplus package (that basically fit distributions). There is something I do not understand about the generic function summary. In the current version on CRAN, there is no NAMESPACE saying S3method(summary, fitdist) . However if we use summary on an object send by fitdist function it works fine... According to R-lang, we have " The most
2010 Oct 03
1
Johnson Distribution Fit
Hi, I am trying to fit a Johnson SB distribution using fitdist function in fitdistrplus Library. I have defined the Johnson SB distribution from ( http://www.ntrand.com/johnson-sb-distribution/) . But it gives me the follwing errors. Any help would be appreciated #xi = xi #lambda =l #delta =d #gamma = g djohn = function(x,xi,l,d,g) (d/(l*sqrt(2*pi)*((x-xi)/l)*(1-((x-xi)/l))))*exp[-0.5*(g +
2011 Aug 01
3
Beta fit returns NaNs
Hi, sorry for repeating the question but this is kind of important to me and i don't know whom should i ask. So as noted before when I do a parameter fit to the beta distr i get: fitdist(vectNorm,"beta"); Fitting of the distribution ' beta ' by maximum likelihood Parameters: estimate Std. Error shape1 2.148779 0.1458042 shape2 810.067515 61.8608126 Warning
2010 Jul 15
1
How do I combine lists of data.frames into a single data frame?
The data.frame is constructed by one of the following functions: funweek <- function(df) if (length(df$elapsed_time) > 5) { rv = fitdist(df$elapsed_time,"exp") rv$year = df$sale_year[1] rv$sample = df$sale_week[1] rv$granularity = "week" rv } funmonth <- function(df) if (length(df$elapsed_time) > 5) { rv =