[R] multinomial regresion, nls

[Mpiktas]

Hi,

Does R have any functions implementing such multinomial regression:

(S_t^A,S_t^B)~MN(N_t-Y_{t-1},P_t^A,P_t^B)

where MN(n,p_1,p_2) is multinomial distribution with parameters n, p_1, p_2.
Here P_t^A and P_t^B are nonlinear functions from predictor variables and
parameters which need to be estimated.

Here A and B are used for notation, they are not parameters.

My second question is about nls capabilities. Can I use lagged response
variable in right side of formula specified in nls. Like this:

nls(y~a*f(B(y)),data=data,start=list(a=1))

where B is lag operator. Or should I just use lagged response variable as
predictor variable:

nls(y~a*f(x),data=data1,start=list(a=1))

data1<-data.frame(y=y,x=c(0,y[1:(length(y)-1)]))

here f is arbitrary function.

Thank you in advance for any answers.

Sincerely,

Vaidotas Zemlys

PS I'm resending this mail, since it seems that it didn't get through the  
first time. I am sorry, if you got 2 messages.