Displaying 20 results from an estimated 1000 matches similar to: "help with simple goodness of fit test"
2008 Feb 18
0
Solved (??) Behaviour of integrate (was 'Poisson-lognormal probab ility calculations')
Hi Again,
I think I've solved my problem, but please tell me if you think I'm wrong,
or you can see a better way!
A plot of the integrand showed a very sharp peak, so I was running into the
integrand "feature" mentioned in the note. I resolved it by limiting the
range of integration as shown here:
--------------------------------------------------
function (x, meanlog = 0,
2008 Feb 15
0
Behaviour of integrate (was 'Poisson-lognormal probability calcul ations')
Hi again,
Adding further information to my own query, this function gets to the core
of the problem, which I think lies in the behaviour of 'integrate'.
-------------------------------------
function (x, meanlog = 0, sdlog = 1, ...) {
require(stats)
integrand <- function(t, x, meanlog, sdlog) dpois(x,t)*dlnorm(t,
meanlog, sdlog)
mapply(function(x, meanlog, sdlog, ...)
#
2010 Apr 28
0
Truncated Lognormal Distribution
Hi!
I have following data which is left truncated say at 10. I am trying to estimate the parameters of the Truncated Lognormal distribution to this data as given below.
(I have referred to R code appearing in an earlier post - http://finzi.psych.upenn.edu/Rhelp10/2008-October/176136.html)
library(MASS)
x <- c(600.62,153.05,70.26,530.42,3440.29,97.45,174.51,168.47, 116.63,36.51, 219.77,
2008 Feb 15
0
Poisson-lognormal probability calculations
Hi,
just for the record, although I don't think it's relevant (!)
-------------------------------------
> sessionInfo()
R version 2.6.0 (2007-10-03)
i386-pc-mingw32
locale:
LC_COLLATE=English_United Kingdom.1252;LC_CTYPE=English_United
Kingdom.1252;LC_MONETARY=English_United
Kingdom.1252;LC_NUMERIC=C;LC_TIME=English_United Kingdom.1252
attached base packages:
[1] stats4 splines
2002 Jul 12
1
Minor bug in dlnorm (PR#1781)
The density of a lognormal should be 0 for negative arguments, but
> dlnorm(-1)
[1] NaN
Warning message:
NaNs produced in: dlnorm(x, meanlog, sdlog, log)
A simple fix is to change dlnorm's definition to:
function (x, meanlog = 0, sdlog = 1, log = FALSE)
.Internal(dlnorm(x*(x>0), meanlog, sdlog, log))
It might be faster to put the same sort of adjustment into the
internal code, but
2009 Aug 07
0
Fitting Truncated Distribution
Dear All,
I know that this topic has been already discussed on this list (see e.g.
http://markmail.org/message/bq2bdxwblwl4rpgf?q=r+fit+truncated+lognormal&page=1&refer=2ufc4fb2eftfwwml#query:r%20fit%20truncated%20lognormal+page:1+mid:7wxgkdxhixotorr5+state:results
for the case of weibull distribution), but I am experiencing some problems.
I deal with truncated distributions (that this to
2003 Aug 28
2
ks.test()
Dear All
I am trying to replicate a numerical application (not computed on R) from an
article. Using, ks.test() I computed the exact D value shown in the article
but the p-values I obtain are quite different from the one shown in the
article.
The tests are performed on a sample of 37 values (please see "[0] DATA"
below) for truncated Exponential, Pareto and truncated LogNormal
2007 Feb 14
0
How to use Rpad
I am a beginner and I don't know how to use Rpad package.
I installed it and opened the following example .Rpad page in Internet
Explorer.
When I clicked "Calculate" button, nothing seems to happen. Can anyone tell
me how to use Rpad?
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN">
<html>
<!-- by Tom Short, EPRI, tshort at epri.com
(c) Copyright 2005 by
2008 May 04
1
Is my understanding of rlnorm correct?
rlnorm takes two 'shaping' parameters: meanlog and sdlog.
meanlog would appear from the documentation to be the log of the mean.
eg if the desired mean is 1 then meanlog=0.
So to generate random values that fit a lognormal distribution I would
do this:
rlnorm(N , meanlog = log(mean) , sdlog = log(sd))
But when I check the mean I don't get it when sdlog>0. Interestingly I
2005 Jun 29
2
MLE with optim
Hello,
I tried to fit a lognormal distribution by using optim. But sadly the output
seems to be incorrect.
Who can tell me where the "bug" is?
test = rlnorm(100,5,3)
logL = function(parm, x,...) -sum(log(dlnorm(x,parm,...)))
start = list(meanlog=5, sdlog=3)
optim(start,logL,x=test)$par
Carsten.
[[alternative HTML version deleted]]
2002 Dec 10
1
Lognormal distribution
I am trying to fit a lognormal distribution to a set of data and test its
goodness of fit with regard to predicted values.
I managed to get so far:
> y <- c(2,6,2,3,6,7,6,10,11,6,12,9,15,11,15,8,9,12,6,5)
> library(MASS)
> fitdistr(y,"lognormal",start=list(meanlog=0.1,sdlog=0.1))
meanlog sdlog
1.94810515 0.57091032
(0.12765945) (0.09034437)
But I would
2012 Jun 03
0
Bug in truncgof package?
Dear Carlos, Duncan and everyone
You may have already sorted the matter by now, but since I have not seen
anything posted since Duncan's reply, here I go. I apologize in advance
for the spam, if it turns out I've missed some post.
I think the test and the implementation of the truncgof package are just
fine. I've done Carlos' experiment (repeatedly generating samples and
testing
2012 Oct 14
0
multivariate lognormal distribution simulation in compositions
Dear All,
thanks to Berend, my question posted yesturday was solved succesfully here: http://r.789695.n4.nabble.com/hep-on-arithmetic-covariance-conversion-to-log-covariance-td4646068.html . I posted the question with the assumption of using the results with rlnorm.rplus() from compositions. Unfortunatelly, I am not getting reasonable enough outcome. Am I applying the results wrongfully? The
2011 Jan 02
1
How to compute the density of a variable that follows a proportional error distribution
Hello,
I am trying to compute the density of a variable k that is either (1)
Normally distributed; (2) Log-Normally distributed; or (3) follows
proportional error distribution. I tried to search R-help and the answer for
normal distribution was easy to find (please see 1c). I am not sure if my
formula for dlnorm is correct (please see 2c below)? I really don't know
what function to use for the
2008 Jul 17
0
How to compute loglikelihood of Lognormal distribution
Hi,
I am trying to learn lognormal mixture models with EM.
I was wondering how does one compute the log likelihood.
The current implementation I have is as follows,
which perform really bad in learning the mixture models.
__BEGIN__
# compute probably density of lognormal.
dens <- function(lambda, theta, k){
temp<-NULL
meanl=theta[1:k]
sdl=theta[(k+1):(2*k)]
2009 May 31
1
Bug in truncgof package?
Dear R-helpers,
I was testing the truncgof CRAN package, found something that looked
like a bug, and did my job: contacted the maintainer. But he did not
reply, so I am resending my query here.
I installed package truncgof and run the example for function ad.test. I
got the following output:
set.seed(123)
treshold <- 10
xc <- rlnorm(100, 2, 2) # complete sample
xt <- xc[xc >=
2014 Oct 15
2
Test K-S con distribuciones LogNormales
Hola Ruben,
Sí precisamente es lo que comentas, en matemáticas no se suele llamar
bucketización (este término se emplea más en informática) sino datos
agrupados. Pero la idea es la que tu mismo dices.
Respecto a las gráficas que has puesto, me han aclarado mucho sobre el
tema, gracias.
Si realizo lo mismo, por ejemplo con nbucket=1000 sigo obteniendo un
p-valor de 1. Es decir, que casi le
2011 Jan 07
0
Fitting an Inverse Gamma Distribution to Survey Data
Hello,
I've been attempting to fit the data below with an inverse gamma
distribution. The reason for this is outside proprietary software (@Risk)
kicked back a Pearson5 (inverse gamma) as the best fitting distribution with
a Chi-Sqr goodness-of-fit roughly 40% better than with a log-normal fit.
Looking up "Inverse gamma" on this forum led me the following post:
2008 Nov 14
0
Error in optim when i call it from a function
Dear R-users
I've got the next problem:
I've got this *function*:
fitcond=function(x,densfun,pcorte,start,...){
myfn <- function(parm,x,pcorte,...) -sum(log(dens(parm,x,pcorte,...)))
Call <- match.call(expand.dots = TRUE)
if (missing(start))
start <- NULL
dots <- names(list(...))
dots <- dots[!is.element(dots, c("upper",
2004 May 01
2
Generating Lognormal Random variables (PR#6843)
Full_Name: Anthony Gichangi
Version: 1.90
OS: Windows XP Pro
Submission from: (NULL) (130.225.131.206)
The function rlnorm generates negative values for lognormal distribution.
x- rlnorm(1000, meanlog = 0.6931472, sdlog = 1)
Regards
Anthony