Re: 2 obvious

*To*: mathgroup at smc.vnet.net*Subject*: [mg115407] Re: 2 obvious*From*: Francisco Gutierrez <fgutiers2002 at yahoo.com>*Date*: Mon, 10 Jan 2011 02:38:36 -0500 (EST)

Many thanks to Darren and others who provided very useful answers to my query. And happy 2011 Fg --- On Tue, 1/4/11, Darren Glosemeyer <darreng at wolfram.com> wrote: > From: Darren Glosemeyer <darreng at wolfram.com> > Subject: [mg115231] Re: 2 obvious > To: mathgroup at smc.vnet.net > Date: Tuesday, January 4, 2011, 6:50 PM > On 12/23/2010 2:55 AM, Francisco > Gutierrez wrote: > > Dear Group: > > Ok, here comes a really silly question. After v. 7, > the statistical capacities of Mathematica have been > substantially boosted. However, I haven't been able to > interpret the simple command LogitModelFit. THe problem is > that the documentation only offers examples with two > independent variables. I have not managed to find how can n > more independent variables can be inserted so that the > command works. Can somebody send me a simple and clear > example? > > > > Let this be a pretext to thank all the incredibly > useful help the members of this list have generously > provided to me and others. Happy holidays, > > Fg > > > > > > > > > > Hi Francisco, > > The data argument is like for other fitting functions. The > independent > (predictor) variables are the first n-1 elements in each > data point and > the last element in the data point is a dependent > (response) variable. > > Here is a list of 5 data points each having two predictors > and one response. > > In[1]:== data == {{10, 4, 0.26}, {8, 3, 0.04}, {2, 0, 0.17}, > {4, 8, 0.09}, > {9, 4, 0.83}}; > > This treats the predictors as x and y in the fitting > > In[2]:== lm == LogitModelFit[data, {x, y}, {x, y}]; > > > and here we get the fitted function and a table of > parameter information > for the fitting. > > In[3]:== lm[{"BestFit", "ParameterTable"}] > > > 1 > Out[3]== {-------------------------------------, > > 2.384 - 0.236963 x + 0.0664776 y > 1 + E > > > Estimate > Standard > Error z\[Hyphen]Statistic > P\[Hyphen]Value} > > 1 -2.384 > 3.41536 > -0.698022 > 0.485163 > > x 0.236963 > 0.388785 > 0.609496 > 0.542196 > > > y -0.0664776 0.529535 > -0.125539 > 0.900097 > > > > I hope this helps. > > Darren Glosemeyer > Wolfram Research > >