[R] mlogit learning error

[R. Michael Weylandt]

There's something in your data that makes the model computationally
singular when you take the various subsettings... Can you provide a
small reproducible example so we can help narrow it down? It looks
like you're using different data for each mlogit though so I'm not
sure how the comparison that v2 & v5 fail while the other works is
relevant though...

Michael

On Thu, Apr 19, 2012 at 4:03 PM, geek girl <geek.girl.only at gmail.com> wrote:
> I am learning five mlogits as follows
>
> v1.model<-mlogit(v1~1|v2+v3+v4+v5, data=mlogit.v1.data, reflevel="1")
> v2.model<-mlogit(v2~1|v1+v3+v4+v5, data=mlogit.v2.data, reflevel="1")
> v3.model<-mlogit(v3~1|v1+v2+v4+v5, data=mlogit.v3.data, reflevel="1")
> v4.model<-mlogit(v4~1|v1+v2+v3+v5, data=mlogit.v4.data, reflevel="1")
> v5.model<-mlogit(v5~1|v1+v2+v3+v4, data=mlogit.v5.data, reflevel="1")
>
> v2 and v5 give me the error below during learning, the other 3 models work
> fine
>
> "Error in solve.default(H, g[!fixed]) : system is computationally singular:
> reciprocal condition number = 1.12239e-16"
>
> What does this error mean?
>
> Thanks
>
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