Path: csiph.com!newsfeed.hal-mli.net!feeder3.hal-mli.net!newsfeed.hal-mli.net!feeder1.hal-mli.net!newsfeed.xs4all.nl!newsfeed2.news.xs4all.nl!xs4all!post.news.xs4all.nl!not-for-mail Return-Path: X-Original-To: python-list@python.org Delivered-To: python-list@mail.python.org X-Spam-Status: OK 0.014 X-Spam-Evidence: '*H*': 0.97; '*S*': 0.00; 'failing': 0.05; 'that?': 0.05; 'python': 0.09; 'friday,': 0.09; 'skip:[ 40': 0.09; 'suggest': 0.11; '2.7': 0.13; '"python': 0.16; 'formula': 0.16; 'googled': 0.16; 'modules,': 0.16; 'received:169.254.2': 0.16; 'received:216.32.181.186': 0.16; 'received:exchangelabs.com': 0.16; 'received:prod.exchangelabs.com': 0.16; 'wrote:': 0.17; 'windows': 0.19; 'math': 0.20; 'to:name:python-list@python.org': 0.20; 'thanks.': 0.21; 'symbolic': 0.22; 'example': 0.23; 'somebody': 0.23; 'to:2**1': 0.23; 'seems': 0.23; 'random': 0.24; 'received:169.254': 0.24; 'header:In-Reply-To:1': 0.25; 'question': 0.27; 'first.': 0.27; 'received:216.32': 0.27; 'post': 0.28; 'url:mailman': 0.29; 'received:169': 0.29; 'header:Received:8': 0.30; 'url:python': 0.32; 'sources': 0.32; 'could': 0.32; 'url:listinfo': 0.32; 'received:10.43': 0.33; 'to:addr:python-list': 0.33; 'received:bigfish.com': 0.35; 'list.': 0.35; 'skip:_ 40': 0.35; 'subject:': 0.36; 'but': 0.36; 'url:org': 0.36; 'email addr:python.org': 0.36; 'thank': 0.36; 'sent:': 0.37; 'data': 0.37; 'subject:: ': 0.38; 'from:': 0.38; 'some': 0.38; 'received:10': 0.38; 'to:addr:python.org': 0.39; 'google': 0.39; 'url:mail': 0.40; 'your': 0.60; 'group,': 0.60; 'first': 0.61; 'received:216': 0.62; 'charset:iso-2022-jp': 0.62; 'email name:python-list': 0.62; 'maximum': 0.63; 'email addr:gmail.com': 0.63; 'dear': 0.66; 'kindly': 0.67; '2013': 0.84; 'dumb': 0.84; 'estimation': 0.84; 'received:ch1ehsmhs008.bigfish.com': 0.84; '1:47': 0.91 X-Forefront-Antispam-Report: CIP:207.46.4.203; KIP:(null); UIP:(null); IPV:NLI; H:SN2PRD0102HT015.prod.exchangelabs.com; RD:none; EFVD:NLI X-SpamScore: -8 X-BigFish: PS-8(zz98dI9371I1503Md87dh1432Izz1d77h1ee6h1202h1e76h1d1ah1d2ahzz17326ah8275bh8275dhz2dh2a8h668h839h945hd25hf0ah1288h12a5h12a9h12bdh137ah13b6h1441h1504h1537h153bh15d0h162dh1631h1758h18e1h1946h1155h) From: tkhan10 To: "subhabangalore@gmail.com" , "python-list@python.org" Subject: RE: Maximum Likelihood Estimation Thread-Topic: Maximum Likelihood Estimation Thread-Index: AQHOAKCw+IUxvximbEmTJ8/ic7h9Z5hlRHIAgAATcACAAAM6kw== Date: Fri, 1 Feb 2013 19:01:37 +0000 References: <68027a3f-5320-44b7-a985-1d213062e2c0@googlegroups.com>, In-Reply-To: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.27.50.24] Content-Type: text/plain; charset="iso-2022-jp" Content-Transfer-Encoding: quoted-printable MIME-Version: 1.0 X-OriginatorOrg: masonlive.gmu.edu X-BeenThere: python-list@python.org X-Mailman-Version: 2.1.15 Precedence: list List-Id: General discussion list for the Python programming language List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , Newsgroups: comp.lang.python Message-ID: Lines: 81 NNTP-Posting-Host: 2001:888:2000:d::a6 X-Trace: 1359747126 news.xs4all.nl 6946 [2001:888:2000:d::a6]:58664 X-Complaints-To: abuse@xs4all.nl Xref: csiph.com comp.lang.python:38050 Hi..=0A= I know this is a very dumb q but actually I am new to python and to this li= st. 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?=0A= Thank you=0A= Subrina=0A= =0A= =0A= ________________________________________=0A= From: Python-list [python-list-bounces+tkhan10=3Dgmu.edu@python.org] on beh= alf of subhabangalore@gmail.com [subhabangalore@gmail.com]=0A= Sent: Friday, February 01, 2013 1:47 PM=0A= To: python-list@python.org=0A= Subject: Re: Maximum Likelihood Estimation=0A= =0A= On Friday, February 1, 2013 11:07:48 PM UTC+5:30, 88888 Dihedral wrote:=0A= > subhaba...@gmail.com=1B$B1w=1B(B 2013=1B$BG/=1B(B2=1B$B7n=1B(B2=1B$BF|@14= |O;=1B(BUTC+8=1B$B>e8a=1B(B1=1B$B;~=1B(B17=1B$BJ,=1B(B04=1B$BICUmF;!'=1B(B= =0A= >=0A= > > Dear Group,=0A= >=0A= > >=0A= >=0A= > >=0A= >=0A= > >=0A= >=0A= > > I am looking for a Python implementation of Maximum Likelihood Estimati= on. If any one can kindly suggest. With a google search it seems scipy,nump= y,statsmodels have modules, but as I am not finding proper example workouts= I am failing to use them.=0A= >=0A= > >=0A= >=0A= > >=0A= >=0A= > >=0A= >=0A= > > I am using Python 2.7 on Windows 7.=0A= >=0A= > >=0A= >=0A= > >=0A= >=0A= > >=0A= >=0A= > > Thanking You in Advance,=0A= >=0A= > >=0A= >=0A= > >=0A= >=0A= > >=0A= >=0A= > > Regards,=0A= >=0A= > >=0A= >=0A= > > Subhabrata=0A= >=0A= >=0A= >=0A= > I suggest you can google "python and symbolic=0A= >=0A= > computation" to get some package for your need first.=0A= >=0A= >=0A= >=0A= > Because it seems that you have to work out some=0A= >=0A= > math formula and verify some random process first=0A= >=0A= > of your data sources with noises .=0A= =0A= Dear Group,=0A= Thanks. I googled and found a new package named Sympy and could generate ML= E graphs. Regards,Subhabrata.=0A= --=0A= http://mail.python.org/mailman/listinfo/python-list=0A=