Hi, I have a question about how to use the mlogit package in R to do analysis
of discrete choice survey data. Our survey is about asking people to choose
from different insurance policies(with two attributes of deductible and
premium).
The code I used to fit mixed logit is:
[1] ml <- mlogit.data (mydata, choice="choice", shape = "wide", id =
"individual",
opposite =c ('deductible', 'premium'),varying = 5:10)
[2] ml.w5 <- mlogit (choice~deductible+premium|0, ml, panel = TRUE,
rpar = c(deductible='ln', premium='ln'),
R = 100, halton = NA, print.level=0)
I try to use lognormal because we hope the coefficients for both deductible
and premium are negative. And I use "opposite" in [1] to reverse the sign
because lognormal is always positive.
But I always get the error warning:
"Error in if (abs(x - oldx) < ftol) { : missing value where TRUE/FALSE
needed
In addition: Warning message: In log(start[ln]) : NaNs produced"
I double check the data and am sure there isn't any missing data. And if I
change the lognormal "ln" to "n" or "cn", it will work without any warning.
Does anyone know how to deal with this? Thank you for your help.
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