R help - Jan 2015 - Mlogit: Error in model.frame.default/ Error in solve.default

Dear R users, 
1) My problem in short: 
Mlogit cannot calculate certain conditional models. 

2) My database: 
The target was a logistical regression analysis and a probability function
which should include generic coefficients and alternative-specific ones. The
database was a survey, the dependent variable consisted of six possible
choices. 
I worked with two databases: 
First, the true survey data (out of the six choices, one is quite dominant
with a share of around 40%, two have around 20% each, and the remaining are
marginal). 
Second, the survey with randomized values for both choice and independent
variables to avoid the possible problems with the less uniform distribution
of the choice variable in the true set. 
Both datasets include 725 individuals with twelve variables due to receive a
generic coefficient and 25 individual ones which should have an alternative
specific coefficient. I have already to note that the problems above emerged
when estimating with only one independent variable. 
Before the estimate, both datasets were brought into the required long
format. The original data in the long format looked ok. 

3) The estimates and the issues. 
I started in both datasets with an estimate with only one variable with a
generic coefficient. I used the following order:  mlogit(choice ~ variable,
data = survey_long) 
R?s comment was ?Error in solve.default(H, g[!fixed]) :   system is
computationally singular: reciprocal condition number = ...?. 
I was able to get an estimate for such a comparably simple model when  using
mlogit(choice ~ variable | 0, data = survey_long). However, the output did
not contain estimates on the alternative specific coefficents for the
intercept. 
I continued by gradually adding variables with generic coefficients. If it
was more than five of them, R?s message was ?Error in solve.default(H,
g[!fixed]) : system is computationally singular: reciprocal condition number
=  ...?. 
One of the variables had the problem ?Error in
model.frame.default(terms(formula, lhs = lhs, rhs = rhs, data = data),  :  
variable lengths differ (found for 'C15_CC_Dist')?. 
I compared the length for all the variables, and it was all the same. 

Another thing: It was impossible to add variables with an alternative
specific coefficient:  ?Error in solve.default(H, g[!fixed]) :    system is
computationally singular: reciprocal condition number =  ...?. 

These statements appeared both when using the true survey as well as when
using the randomized data. 

Does anyone have any comment or help on that? What can I do? I can send the
datasets if required. 

Any comment would be helpful. 

Best regards, 

LvC




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