Displaying 20 results from an estimated 6000 matches similar to: "How to obtain parameters of a mixture model of two lognormal distributions"
2013 Mar 18
2
Fit a mixture of lognormal and normal distributions
Hello
I am trying to find an automated way of fitting a mixture of normal and log-normal distributions to data which is clearly bimodal.
Here's a simulated example:
x.1<-rnorm(6000, 2.4, 0.6)x.2<-rlnorm(10000, 1.3,0.1)X<-c(x.1, x.2)
hist(X,100,freq=FALSE, ylim=c(0,1.5))lines(density(x.1), lty=2, lwd=2)lines(density(x.2), lty=2, lwd=2)lines(density(X), lty=4)
Currently i am using
2003 Apr 09
3
plotting the lognormal density curve
I am trying to plot a lognormal density curve on top of an existing
histogram. Can anybody suggest a simple way to do this? Even if someone
could just explain how to plot a regular normal density curve on top of an
existing histogram, it would be a big help.
Also, is there some way to search through the R-help archives other than
simple browsing?
Thank you so much. Your help and time is greatly
2011 Feb 02
2
clustering with finite mixture model
Dear R-help,
I am doing clustering via finite mixture model. Please suggest some packages in
R to find clusters via finite mixture model with continuous variables. And
also I wish to verify the distributional properties of the mixture distributions
by fitting the model with lognormal, gamma, exponentials etc,.
Thanks in advance,
warm regards,Ms.Karunambigai M
PhD Scholar
Dept. of Biostatistics
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
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
2008 Oct 07
3
Fitting weibull, exponential and lognormal distributions to left-truncated data.
Dear All,
I have two questions regarding distribution fitting.
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:
fitdistr<-(x,"weibull")
However, this does not take into consideration the truncation at x=1. I
read another posting in this
2009 May 29
1
Mean of lognormal in base-2
Hi, Does anyone know what the mean value of a lognormal distribution in base-2 is? I am simulating stochastic population growth and if I were working in base-e, I would do:lambda <- 1.1 #multiplicative growth rates <- 0.6 #stochasticity (std. dev)lognormal <- rlnorm(100000, log(lambda) - (s^2)/2, s)## or lognormal <- exp( rnorm( 100000, log(lambda) - (s^2)/2,
2006 Aug 05
1
AIC for lognormal model
Dear all,
I want to compare some different models for a dataset by QQ plots and AIC. I get the following AICs:
- linear model: 19759.66
- GAMLSS model: 18702.7
- linear model with lognormal response: -7862.182
The QQ plots show that the lognormal model fits better than the linear model, but still much worse than the GAMLSS. So, in my opinion, the AIC of the lognormal model should be between the
2007 Mar 23
1
generating lognormal variables with given correlation
Dear R users
I use simulated data to evaluate a model by sampling the parameters in
my model from lognormal distributions.
I would like these (lognormal distributed) parameters to be correlated,
that is, I would like to have pairwise samples of 2 parameters with a
given correlation coefficient.
I have seen that a covariance matrix can be fixed when generating random
variables from a
2012 Aug 31
3
fitting lognormal censored data
Hi ,
I am trying to get some estimator based on lognormal distribution when we have left,interval, and right censored data. Since, there is now avalible pakage in R can help me in this, I had to write my own code using Newton Raphson method which requires first and second derivative of log likelihood but my problem after runing the code is the estimators were too high. with this email ,I provide
2012 Aug 29
2
Estimation parameters of lognormal censored data
Hi, I am trying to get the maximum likelihood estimator for lognormal distribution with censored data;when we have left, interval and right censord. I built my code in R, by writing the deriving of log likelihood function and using newton raphson method but my estimators were too high " overestimation", where the values exceed the 1000 in some runing of my code.
is there any one can
2010 Dec 27
3
Gamma & Lognormal Model
Dear,
I'm very new to R Gui and I have to make an assignment on Gamma Regressions.
Surfing on the web doesn't help me very much so i hope this forum may be a
step forward.
The question sounds as follows:
The data set is in the library MASS
first install library(MASS)
then type data(mammals)
attach(mammals)
Assignment:
Fit the gamma model and lognormal model for the mammals data.
2005 Jan 31
2
ML-Fit for truncated distributions
Hello,
maybe that my Question is a "beginner"-Question, but up to now, my research
didn't bring any useful result.
I'm trying to fit a distribution (e.g. lognormal) to a given set of data
(ML-Estimation). I KNOW about my data that there is a truncation for all
data below a well known threshold. Is there an R-solution for an
ML-estimation for this kind of data-problem? As
2008 Feb 22
1
fitting a lognormal distribution using cumulative probabilities
Dear all,
I'm trying to estimate the parameters of a lognormal distribution fitted
from some data.
The tricky thing is that my data represent the time at which I recorded
certain events. However, in many cases I don't really know when the event
happened. I' only know the time at which I recorded it as already happened.
Therefore I want to fit the lognormal from the cumulative
2010 Aug 01
2
Lognormal distribution - Range Factor
Hi, What does it mean to say Lognormal distribution with a mean of 1.03E-6
with a range factor of 100 ? How can I find the lognormal distribution
paramters from this information?
Thanks, Tims
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2004 Dec 13
1
AIC, glm, lognormal distribution
I'm attempting to do model selection with AIC, using a glm and a lognormal
distribution, but:
fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian(link="log"))
## gives the same result as either of the following:
fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian)
fit1<-lm(BA~Year,data=pdat.sp1.65.04)
fit1
#Coefficients:
#(Intercept) Year2004
# -1.6341
2009 Jan 16
3
Fitting of lognormal distribution to lower tail experimental data
Hi,
I am beginner with R and need firm guidance with my problem. I have seen
some other threads discussing the subject of right censored data, but I am
not sure whether or not this problem can be regarded as such.
Data:
I have a vector with laboratory test data (strength of wood specimens,
example attached as txt-file). This data is the full sample. It is a
common view that this kind of data
2010 Mar 26
1
Poisson Lognormal
Hi R Users,
I'm going to estimate via. ML the parameters in Poisson Lognormal
model. The model is:
x | lambda ~ Poisson(lambda)
lambda ~ Lognormal(a,b)
Unfortunately, I haven't found a useful package allowing for such
estimation. I tried to use "poilog" package, but there is no equations
and it's hard to understand what exactly this package really does.
Using it I get the
2011 Nov 01
1
low sigma in lognormal fit of gamlss
Hi,
I'm playing around with gamlss and don't entirely understand the sigma
result from an attempted lognormal fit.
In the example below, I've created lognormal data with mu=10 and sigma=2.
When I try a gamlss fit, I get an estimated mu=9.947 and sigma=0.69
The mu estimate seems in the ballpark, but sigma is very low. I get similar
results on repeated trials and with Normal and
2007 Sep 04
0
ML fit of pareto and lognormal distributions to grouped data
Dear list members,
I have a set of claims data, which are in ranges and the shape of the
distribution is relatively different. I have looked through R help
threads and found out that an ideal way is suggested for the gamma
distribution ML fitting for grouped data.
I just wonder if there is any method that works for lognormal or
pareto distribution?
An example would be: