Tagged Questions
5
votes
1answer
435 views
Alternatives to multinomial logistic regression
I have been using a multinomial logistic regression to examine the correlates of school choice. There are three possibilities for the dependent variable: government school, private school, and NGO ...
2
votes
0answers
69 views
Using minimum description length for a categorical distribution
My data is as follows: in a routing node (check figure ), I can see the entry and exit gate of each packet, so I have pairs like this:
(1,5) (2,5) (1,6)...
...
1
vote
1answer
557 views
Regression technique for data comprised of categorical explanatory variables & a continuous response variable
i suppose one way to characterize data is by a combination of the variable types that comprises it:
...
1
vote
0answers
82 views
Identification of significant variables where dependent variable is categorical
I have a set of some 50,000 data points. There is one dependent variable which is categorical in nature and there are some 100 possible explanatory variables. Out of these 100, I have to select some ...
3
votes
0answers
59 views
Graphical nominal model
Suppose I have a set of $k$ matrices.
$$
\epsilon = A_1,A_2,...,A_k
$$
Each column of $A$ is categorical vector.
$$
A = v_1,v_2,...,v_n
$$
I want to find the mapping
$$
f: A ...
5
votes
1answer
363 views
If a factor variable is to be dropped in model selection, should all levels be dropped simultaneously? If so, why?
In answer to a previous question factor pooling in model selection was discussed.
If a factor or categorical variable is to be dropped in model selection, should all levels be dropped simultaneously? ...
4
votes
4answers
327 views
Incorporating boolean data into analysis
I have a data set of about 3,000 field observations.
The data collected is divided into 20 variables (real numbers), 30 boolean variables, and 10 or so look up variables and one "answer" variable
...
