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 =