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From: Luca Di Simone on 4 Nov 2009 10:46 I am working with glmfit to perform probit regressions. I want to regress my y on just a costant but the glmfit points out that the limit is reached. My syntax is; [beta dev stat]=glmfit(x,[y n],'binomial','probit') if x has not regressors, what's the function's input in place of x? and if the regression contains already a (default) constant, in such a case, how can I exclude the constant? thanks for your help Luca
From: Peter Perkins on 4 Nov 2009 10:57 Luca Di Simone wrote: > I am working with glmfit to perform probit regressions. I want to regress my y on just a costant but the glmfit points out that the limit is reached. > > My syntax is; > [beta dev stat]=glmfit(x,[y n],'binomial','probit') > > if x has not regressors, what's the function's input in place of x? and if the regression contains already a (default) constant, in such a case, how can I exclude the constant? As the help says, >> help glmfit GLMFIT Fit a generalized linear model. [snip] 'constant' - specify as 'on' (the default) to include a constant term in the model, or 'off' to omit it. The coefficient of the constant term is the first element of B. Or you can do this: x = zeros(size(y,1),0) glmfit(x,[y n],'binomial','link','probit') But why are you using GLMFIT if you don't have any predictor variables? The only reason I can think of would be to compute some version of r-squared.
From: Luca Di Simone on 4 Nov 2009 11:26
I am computing the mcfadden r^2 and I have to calculate the log likelihood of a model with only intercept. Now I used the vector of zeros as only regressor but the output of the function is that the matrix is singular to working precision. While if I perform the regression on an specific regressor the results have not this problem. How can I do? thanks Luca Peter Perkins <Peter.Perkins(a)MathRemoveThisWorks.com> wrote in message <hcs88q$qgf$1(a)fred.mathworks.com>... > Luca Di Simone wrote: > > I am working with glmfit to perform probit regressions. I want to regress my y on just a costant but the glmfit points out that the limit is reached. > > > > My syntax is; > > [beta dev stat]=glmfit(x,[y n],'binomial','probit') > > > > if x has not regressors, what's the function's input in place of x? and if the regression contains already a (default) constant, in such a case, how can I exclude the constant? > > As the help says, > > >> help glmfit > GLMFIT Fit a generalized linear model. > [snip] > 'constant' - specify as 'on' (the default) to include a constant > term in the model, or 'off' to omit it. The coefficient of the > constant term is the first element of B. > > Or you can do this: > > x = zeros(size(y,1),0) > glmfit(x,[y n],'binomial','link','probit') > > But why are you using GLMFIT if you don't have any predictor variables? The only reason I can think of would be to compute some version of r-squared. |