On Wed, 8 Oct 2008, Gough Lauren wrote:
Hi,
Thank you very much for your reply. This seems to be working OK when
fitting weibull and lognormal distributions. However, fitdistr now
requires me to include start values:
As documented.
ltwei<-function(x,shape,scale,log=FALSE){
+ dweibull(x,shape,scale,log)/pweibull(1,shape,scale,lower=FALSE)
+ }
ltweifit<-fitdistr(x,ltwei) # x is observed data
Error in fitdistr(x, ltwei) : 'start' must be a named list
ltweifit<-fitdistr(x,ltwei,start=list(shape=0.5,scale=0.5))
There were 34 warnings (use warnings() to see them)
ltweifit
shape scale
1.11108278 13.00703630
( 0.01936651) ( 0.42897340)
Is there anyway I can fit to truncated data without having to name start
values? Alternatively, is there any recommended technique for choosing
sensible start values?
Not really, depends how heavy the truncation is.
Further, when I try to fit an exponential distribution I get an error
message:
But a truncated exponential is just a shifted exponential and has one
parameter -- you gave it two! Just fit an exponential to x-1.
ltexp<-function(x,rate,log=FALSE){
+ dexp(x,rate,log)/pexp(1,rate,lower=FALSE)
+ }
ltexpfit<-fitdistr(x,ltexp)
Error in fitdistr(x, ltexp) : 'start' must be a named list
ltexpfit<-fitdistr(x,ltexp,start=list(0.1))
Warning message:
In optim(x = c(2.541609, 1.436143, 4.600524, 6.437174, 2.84974, :
one-diml optimization by Nelder-Mead is unreliable: use optimize
ltexpfit
Error in dn[[2]] : subscript out of bounds
This error message seems to occur regardless of the start value used.
Do you know why this is?
Sorry to pester you again, and apologies if I am asking silly questions
- my knowledge of R and probability distributions (except the normal!)
are rather limited!
Best wishes
Lauren
-----Original Message-----
From: Prof Brian Ripley [mailto:[EMAIL PROTECTED]
Sent: 07 October 2008 12:25
To: [EMAIL PROTECTED]
Cc: Gough Lauren; vito muggeo; r-help@r-project.org
Subject: Re: [R] Fitting weibull, exponential and lognormal
distributions to left-truncated data.
On Tue, 7 Oct 2008, [EMAIL PROTECTED] wrote:
I have several datasets, all left-truncated at x=1, that I am
attempting
to fit distributions to (lognormal, weibull and exponential). I had
been using fitdistr in the MASS package as follows:
A possible solution is to use the survreg() in the survival package
without specifying the covariates, i.e.
library(survival)
survreg(Surv(..)~1, dist="weibull")
where Surv(..) accepts information about "times",
censoring/truncation variables and dist allows to specify alternative
distributions.
See ?Surv e ?survreg
The survival package is mostly targeted at right-censored data. The
NADA package provides wrappers for many of the survival routines so
they work with left-censored data.
Left-censoring and left-truncation are not the same thing. With
left-censoring you see that you had observations < 1, and with
left-truncation you do not (at least how the terms are usually applied:
occasionally the meanings are reversed).
For left-truncation it is relatively easy, e.g.
ltwei <- function(x, shape, scale = 1, log = FALSE)
dweibull(x, shape, scale, log)/pweibull(1, shape, scale,
lower=FALSE)
and use this in fitdistr.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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