A plot of the of the PDF logit estimator

Hello,

I estimated the logit model, but I need to plot the distribution (PDF) underlying the logit model. Could you please provide some help on this?

Thanks!

 

1 Answer



0



Hello,

If I am interpreting your question correctly you want to be able to graph the underlying logistic function y = e^(b0+xb)/(1+e^(b0 + xb)). I am not sure how you have estimated your logit model but I can provide a general explanation. Suppose we have estimated the logit model of the dependent variable, y, on the dependent variable, x. The model yields two estimates, an intercept, b0 and a coefficient, b. In order to create your graph, you need to first generate y_pred = b0 + xb. However, for the sake of the graph, the y_pred should be created using a sorted x.


x_sorted = sortc(x,1);
y_pred = b0 + x_sorted.*b;

Next, y_pred needs to be transformed logistically:


y_gr = exp(y_pred)./(1+ exp(y_pred));

This can now be directly graphed using the plotXY function.


plotXY(x_sorted, y_gr);

If you provide more information regarding how you estimated the logit model or provide code, I would be happy to provide a more detailed and specific explanation.

Your Answer

1 Answer

0

Hello,

If I am interpreting your question correctly you want to be able to graph the underlying logistic function y = e^(b0+xb)/(1+e^(b0 + xb)). I am not sure how you have estimated your logit model but I can provide a general explanation. Suppose we have estimated the logit model of the dependent variable, y, on the dependent variable, x. The model yields two estimates, an intercept, b0 and a coefficient, b. In order to create your graph, you need to first generate y_pred = b0 + xb. However, for the sake of the graph, the y_pred should be created using a sorted x.


x_sorted = sortc(x,1);
y_pred = b0 + x_sorted.*b;

Next, y_pred needs to be transformed logistically:


y_gr = exp(y_pred)./(1+ exp(y_pred));

This can now be directly graphed using the plotXY function.


plotXY(x_sorted, y_gr);

If you provide more information regarding how you estimated the logit model or provide code, I would be happy to provide a more detailed and specific explanation.


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