[R] Compare two normal to one normal
Bert Gunter
bgunter.4567 at gmail.com
Tue Sep 22 22:48:45 CEST 2015
I'll be brief in my reply to you both, as this is off topic.
So what? All this statistical stuff is irrelevant baloney(and of
questionable accuracy, since based on asymptotics and strong
assumptions, anyway) . The question of interest is whether a mixture
fit better suits the context, which only the OP knows and which none
of us can answer.
I know that many will disagree with this -- maybe a few might agree --
but please send all replies, insults, praise, and learned discourse to
me privately, as I have already occupied more space on the list than
I should.
Cheers,
Bert
Bert Gunter
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
-- Clifford Stoll
On Tue, Sep 22, 2015 at 1:35 PM, Mark Leeds <markleeds2 at gmail.com> wrote:
> That's true but if he uses some AIC or BIC criterion that penalizes the
> number of parameters,
> then he might see something else ? This ( comparing mixtures to not mixtures
> ) is not something I deal with so I'm just throwing it out there.
>
>
>
>
> On Tue, Sep 22, 2015 at 4:30 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote:
>>
>> Two normals will **always** be a better fit than one, as the latter
>> must be a subset of the former (with identical parameters for both
>> normals).
>>
>> Cheers,
>> Bert
>>
>>
>> Bert Gunter
>>
>> "Data is not information. Information is not knowledge. And knowledge
>> is certainly not wisdom."
>> -- Clifford Stoll
>>
>>
>> On Tue, Sep 22, 2015 at 1:21 PM, John Sorkin
>> <JSorkin at grecc.umaryland.edu> wrote:
>> > I have data that may be the mixture of two normal distributions (one
>> > contained within the other) vs. a single normal.
>> > I used normalmixEM to get estimates of parameters assuming two normals:
>> >
>> >
>> > GLUT <- scale(na.omit(data[,"FCW_glut"]))
>> > GLUT
>> > mixmdl = normalmixEM(GLUT,k=1,arbmean=TRUE)
>> > summary(mixmdl)
>> > plot(mixmdl,which=2)
>> > lines(density(data[,"GLUT"]), lty=2, lwd=2)
>> >
>> >
>> >
>> >
>> >
>> > summary of normalmixEM object:
>> > comp 1 comp 2
>> > lambda 0.7035179 0.296482
>> > mu -0.0592302 0.140545
>> > sigma 1.1271620 0.536076
>> > loglik at estimate: -110.8037
>> >
>> >
>> >
>> > I would like to see if the two normal distributions are a better fit
>> > that one normal. I have two problems
>> > (1) normalmixEM does not seem to what to fit a single normal (even if I
>> > address the error message produced):
>> >
>> >
>> >> mixmdl = normalmixEM(GLUT,k=1)
>> > Error in normalmix.init(x = x, lambda = lambda, mu = mu, s = sigma, k =
>> > k, :
>> > arbmean and arbvar cannot both be FALSE
>> >> mixmdl = normalmixEM(GLUT,k=1,arbmean=TRUE)
>> > Error in normalmix.init(x = x, lambda = lambda, mu = mu, s = sigma, k =
>> > k, :
>> > arbmean and arbvar cannot both be FALSE
>> >
>> >
>> >
>> > (2) Even if I had the loglik from a single normal, I am not sure how
>> > many DFs to use when computing the -2LL ratio test.
>> >
>> >
>> > Any suggestions for comparing the two-normal vs. one normal distribution
>> > would be appreciated.
>> >
>> >
>> > Thanks
>> > 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)
>> >
>> >
>> > Confidentiality Statement:
>> > This email message, including any attachments, is for ...{{dropped:12}}
>>
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>
>
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