Maximum Likelihood Estimation

[subhabangalore]

Dear Group,

I am looking for a Python implementation of Maximum Likelihood Estimation. If any one can kindly suggest. With a google search it seems scipy,numpy,statsmodels have modules, but as I am not finding proper example workouts I am failing to use them.

I am using Python 2.7 on Windows 7.

Thanking You in Advance,

Regards,
Subhabrata

 

[88888 Dihedral]

(e-mail address removed)æ–¼ 2013å¹´2月2日星期六UTC+8上åˆ1時17分04秒寫é“：

Dear Group,



I am looking for a Python implementation of Maximum Likelihood Estimation.. If any one can kindly suggest. With a google search it seems scipy,numpy,statsmodels have modules, but as I am not finding proper example workouts Iam failing to use them.



I am using Python 2.7 on Windows 7.



Thanking You in Advance,



Regards,

Subhabrata

I suggest you can google "python and symbolic
computation" to get some package for your need first.

Because it seems that you have to work out some
math formula and verify some random process first
of your data sources with noises .

 

[subhabangalore]

(e-mail address removed)æ–¼ 2013å¹´2月2日星期六UTC+8上åˆ1時17分04秒寫é“：




I suggest you can google "python and symbolic

computation" to get some package for your need first.



Because it seems that you have to work out some

math formula and verify some random process first

of your data sources with noises .

Dear Group,
Thanks. I googled and found a new package named Sympy and could generate MLE graphs. Regards,Subhabrata.

 

[Michael Torrie]

Dear Group, Thanks. I googled and found a new package named Sympy and
could generate MLE graphs. Regards,Subhabrata.

My hat's off to you for actually interpreting the 88888 dihedral robot's
randomly-created response in a way that actually helped you find the
solution to your problem! I think that's a python first around here.

Most people on this list consider 88888 dihedral to be a badly
programmed bot.

 

[tkhan10]

Hi..
I know this is a very dumb q but actually I am new to python and to this list. I want to post a question about geographic masking but cannot find out how to post it. Would somebody please suggest me how to do that?
Thank you
Subrina


________________________________________
From: Python-list [[email protected]] on behalf of (e-mail address removed) [[email protected]]
Sent: Friday, February 01, 2013 1:47 PM
To: (e-mail address removed)
Subject: Re: Maximum Likelihood Estimation

(e-mail address removed)$B1w(B 2013$BG/(B2$B7n(B2$BF|@14|O;(BUTC+8$B>e8a(B1$B;~(B17$BJ,(B04$BICUmF;!'(B




I suggest you can google "python and symbolic

computation" to get some package for your need first.



Because it seems that you have to work out some

math formula and verify some random process first

of your data sources with noises .

Dear Group,
Thanks. I googled and found a new package named Sympy and could generate MLE graphs. Regards,Subhabrata.

 

[Jerry Hill]

Most people on this list consider 88888 dihedral to be a badly
programmed bot.

For what it's worth, I think it's a very cleverly programmed bot. It
usually makes just enough sense for me to wonder if there really is a
human being behind the keyboard.

 

[88888 Dihedral]

在 2013å¹´2月2日星期六UTC+8上åˆ2æ—¶47分22秒，[email protected]写é“：

Dear Group,

Thanks. I googled and found a new package named Sympy and could generate MLE graphs. Regards,Subhabrata.

Well,just reveal more about your problems.

But if you are concerned with some commercial
problems, then it is not the novice apprentice
level jokes.

Then, maybe you can just give some outline of
the problem.

 

[Steven D'Aprano]

Hi..
I know this is a very dumb q but actually I am new to python and to this
list. I want to post a question about geographic masking but cannot find
out how to post it. Would somebody please suggest me how to do that? Thank
you Subrina

Are you using email or Usenet?

In your email client:

1) Create a new email message;

2) Type the To address (e-mail address removed)

3) Type a meaningful subject line such as "Geographic Masking in Python"

4) Type your message.

5) Hit send.

Or, if you are using Usenet, in your news client:

1) Create a new news post;

2) Type the To address comp.lang.python;

3) Type a meaningful subject line such as "Geographic Masking in Python"

4) Type your message.

5) Hit send.

 

[subhabangalore]

Dear Group,



I am looking for a Python implementation of Maximum Likelihood Estimation.. If any one can kindly suggest. With a google search it seems scipy,numpy,statsmodels have modules, but as I am not finding proper example workouts Iam failing to use them.



I am using Python 2.7 on Windows 7.



Thanking You in Advance,



Regards,

Subhabrata

Dear Sir,
The room would take care of you. They still guide me and sometimes the way they rebuke you have to see. You are in a nice room, you'd learn soon. It was bot? If you are testing please let me know I'd like to be part of the testing, and if you suggest may volunteer to send queries.
Regards,
Subhabrata.

 

[Wolfgang Keller]

I am looking for a Python implementation of Maximum Likelihood

Estimation. If any one can kindly suggest. With a google search it
seems scipy,numpy,statsmodels have modules, but as I am not finding
proper example workouts I am failing to use them.

For statistics I would suggest using R (http://www.r-project.org/)
through RPy (http://rpy.sourceforge.net/).

Both have dedicated mailinglists as well as extensive documentation.

Sincerely,

Wolfgang

 

[Oscar Benjamin]

For statistics I would suggest using R (http://www.r-project.org/)
through RPy (http://rpy.sourceforge.net/).

Both have dedicated mailinglists as well as extensive documentation.

I agree with Wolfgang that R is likely to be able to do what you want
and that you may have better luck asking this kind of question on
their mailing lists (or on the scipy mailing list).

In any case, though, you will need to be more specific about what you
mean. Maximum Likelihood Estimation (MLE) is a sufficiently vague
topic that there cannot really be an "implementation" of it. What kind
of model/data are you working with? Or are you working with pure
probability distributions? What kind of parameters are you trying to
find? Are the parameters you are trying to choose discrete or
continuous? Are you trying to find one parameter or several
simultaneously? Are you able to find an analytic solution that
transforms your MLE problem into a specific kind of mathematical
problem, such as solving a system of linear equations?

Assuming that you are able to compute directly the likelihood (or
log-likelihood) of whatever it is you are interested in, then your MLE
problem is simply an optimisation problem, so you may have better luck
searching for implementations of optimisation (you will still need to
answer the questions above to be able choose an optimisation method).


Oscar