I am running normalmixEM:
mixmdlscaled <- normalmixEM(data$FCWg)
summary(mixmdlscaled)
plot(mixmdlscaled,which=2)
If I run the program multiple times, I get widely different results:
> mixmdlscaled <- normalmixEM(data$FCWg)
number of iterations= 41
> summary(mixmdlscaled)
summary of normalmixEM object:
comp 1 comp 2
lambda 0.0818928 0.918107
mu 0.6575938 0.740870
sigma 0.0070562 0.178410
loglik at estimate: 56.87445
> plot(mixmdlscaled,which=2)
> mixmdlscaled <- normalmixEM(data$FCWg)
number of iterations= 357
> summary(mixmdlscaled)
summary of normalmixEM object:
comp 1 comp 2
lambda 0.959912 0.0400879
mu 0.722022 1.0220719
sigma 0.165454 0.0131391
loglik at estimate: 53.66051
> plot(mixmdlscaled,which=2)
I understand that when run without specifying various parameters (e.g. mu, or
sigma) values are chosen randomly from a normal distribution with center(s)
determined from binning the data. Despite this, would not one expect the
results to be similar? If one is not to expect similar results, how can I get a
solution in which I can have confidence? Should I run the program multiple
times and take the average of the results? Should I look for the solution with
the best log likelihood?
Thank you,
John
John David Sorkin M.D., Ph.D.
Professor of Medicine
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology and Geriatric
Medicine
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)
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