I'm trying to do discrete choice modeling on the below data. Basically, 30 customers have 16 different choices of pizza. They can choose more than 1 type of pizza and the ones they choose is indicated by choice variable.
pizza cust choice pan thin pineapple veggie sausage romano mozarella oz
1 1 Cust1 0 1 0 1 0 0 1 0 1
2 2 Cust1 1 0 1 1 0 0 0 0 0
3 3 Cust1 0 0 0 1 0 0 0 1 1
4 4 Cust1 1 0 1 1 0 0 0 0 0
5 5 Cust1 1 1 0 0 1 0 0 0 1
6 6 Cust1 0 0 1 0 1 0 1 0 0
7 7 Cust1 0 0 0 0 1 0 0 0 1
8 8 Cust1 1 0 1 0 1 0 0 1 0
9 9 Cust1 0 1 0 0 0 1 0 1 0
10 10 Cust1 1 0 1 0 0 1 0 0 1
11 11 Cust1 0 0 0 0 0 1 1 0 0
12 12 Cust1 0 0 1 0 0 1 0 0 1
13 13 Cust1 0 1 0 0 0 0 0 0 0
14 14 Cust1 1 0 1 0 0 0 0 1 1
15 15 Cust1 0 0 0 0 0 0 0 0 0
16 16 Cust1 0 0 1 0 0 0 1 0 1
17 1 Cust10 0 1 0 1 0 0 1 0 1
18 2 Cust10 0 0 1 1 0 0 0 0 0
19 3 Cust10 0 0 0 1 0 0 0 1 1
20 4 Cust10 0 0 1 1 0 0 0 0 0
When I use the below command to transform my data. I tried making few changes here like adding chid.var = "chid" and alt.levels=c(1:16). If I use both alt.levels and alt.var it gives me an error saying pizza already exists and will be replaced. However, I get no error if I use either of them.
pz <- mlogit.data(pizza,shape = "long",choice = "choice",
varying = 4:8, id = "cust", alt.var = "pizza")
Finally, when I use the mlogit command, I get this error.
mlogit(choice ~ pan + thin + pineapple + veggie + sausage + romano + mozarella + oz, pz)
Error in solve.default(H, g[!fixed]) :
system is computationally singular: reciprocal condition number = 8.23306e-19
This is my first post on stackoverflow. I visit this site very often and so far never needed to post as I found solutions already. I went through almost all similar posts like this one but in vain. I'm new to discrete choice modeling so I don't know if I'm making any fundamental mistake here.
Also, I'm not really sure what chid.var does.