Path: csiph.com!newsfeed.hal-mli.net!feeder3.hal-mli.net!newsfeed.hal-mli.net!feeder2.hal-mli.net!newsfeed.xs4all.nl!newsfeed4.news.xs4all.nl!xs4all!newsgate.cistron.nl!newsgate.news.xs4all.nl!post.news.xs4all.nl!not-for-mail
Return-Path: <torriem@gmail.com>
X-Original-To: python-list@python.org
Delivered-To: python-list@mail.python.org
X-Spam-Status: OK 0.008
X-Spam-Evidence: '*H*': 0.98; '*S*': 0.00; 'failing': 0.05; 'badly': 0.07; 'python': 0.09; 'friday,': 0.09; 'suggest': 0.11; '"python': 0.16; '8bit%:72': 0.16; 'formula': 0.16; 'from:addr:torriem': 0.16; 'from:name:michael torrie': 0.16; 'googled': 0.16; 'interpreting': 0.16; 'modules,': 0.16; 'problem!': 0.16; 'wrote:': 0.17; '>>>': 0.18; 'math': 0.20; 'thanks.': 0.21; 'symbolic': 0.22; 'example': 0.23; 'seems': 0.23; 'random': 0.24; 'header:In-Reply-To:1': 0.25; 'header:User-Agent:1': 0.26; 'am,': 0.27; 'first.': 0.27; 'sources': 0.32; 'could': 0.32; 'to:addr :python-list': 0.33; 'list': 0.35; 'received:org': 0.36; 'but': 0.36; 'message-id:@gmail.com': 0.36; 'data': 0.37; 'subject:: ': 0.38; 'some': 0.38; 'to:addr:python.org': 0.39; 'received:192': 0.39; 'google': 0.39; 'received:192.168': 0.40; 'header:Received:5': 0.40; 'think': 0.40; 'your': 0.60; 'group,': 0.60; 'most': 0.61; 'first': 0.61; 'maximum': 0.63; 'email addr:gmail.com': 0.63; 'dear': 0.66; 'kindly': 0.67; '2013': 0.84
X-Virus-Scanned: amavisd-new at torriefamily.org
Date: Fri, 01 Feb 2013 11:59:03 -0700
From: Michael Torrie <torriem@gmail.com>
User-Agent: Mozilla/5.0 (X11; Linux i686; rv:10.0.12) Gecko/20130105 Thunderbird/10.0.12
MIME-Version: 1.0
To: python-list@python.org
Subject: Re: Maximum Likelihood Estimation
References: <e7aa8874-3692-4e32-ba52-5f4719761c24@googlegroups.com> <68027a3f-5320-44b7-a985-1d213062e2c0@googlegroups.com> <e59815da-c08a-4cca-af88-7d148a7bceaa@googlegroups.com>
In-Reply-To: <e59815da-c08a-4cca-af88-7d148a7bceaa@googlegroups.com>
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
X-BeenThere: python-list@python.org
X-Mailman-Version: 2.1.15
Precedence: list
List-Id: General discussion list for the Python programming language <python-list.python.org>
List-Unsubscribe: <http://mail.python.org/mailman/options/python-list>, <mailto:python-list-request@python.org?subject=unsubscribe>
List-Archive: <http://mail.python.org/pipermail/python-list/>
List-Post: <mailto:python-list@python.org>
List-Help: <mailto:python-list-request@python.org?subject=help>
List-Subscribe: <http://mail.python.org/mailman/listinfo/python-list>, <mailto:python-list-request@python.org?subject=subscribe>
Newsgroups: comp.lang.python
Message-ID: <mailman.1282.1359745161.2939.python-list@python.org>
Lines: 23
NNTP-Posting-Host: 2001:888:2000:d::a6
X-Trace: 1359745161 news.xs4all.nl 6933 [2001:888:2000:d::a6]:49895
X-Complaints-To: abuse@xs4all.nl
Xref: csiph.com comp.lang.python:38048

On 02/01/2013 11:47 AM, subhabangalore@gmail.com wrote:
> On Friday, February 1, 2013 11:07:48 PM UTC+5:30, 88888 Dihedral
> wrote:
>> subhaba...@gmail.com於 2013年2月2日星期六UTC+8上午1時17分04秒寫道：
>>> 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 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.

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.