 Usage:  myfit = glmmultlo(x,y{,opt})  
 
 Input:

  x                      n x r matrix, the predictor variables. 
                         Individual-specific variables form single 
                         columns of x. Alternative-specific variables 
                         must be evaluated for each alternative and 
                         are to be stored in blocks of m subsequent 
                         columns. The optional parameters opt.indiv 
                         and opt.alter define which columns belong 
                         to which group. Without these optional 
                         parameters, all columns of x are interpreted 
                         as individual-specific. 
                         
  y                      n x 1 vector or n x m matrix. If y is vector 
                         (numeric or string), the different 
                         realizations are considered to be the 
                         alternatives. If y is matrix, it should 
                         contain 0/1 dummies, with 1 in the j-th column 
                         indicating that alternative j (in 1 ... m) has 
                         been chosen. 
                         
  opt                    optional, a list with optional input. The macro 
                         "glmopt" can be used to set up this parameter. 
                         The order of the list elements is not important. 
                         Parameters which are not given are replaced by 
                         defaults (see below). 
                         
  opt.shf                integer, if exists and =1, some output is produced 
                         which indicates how the iteration is going on. 
                         
  opt.miter              integer, maximal number of iterations. The default 
                         is 10. 
                         
  opt.cnv                scalar, convergence criterion. The default is 0.0001. 
                         
  opt.indiv              indices of columns of x (=variables) which are 
                         individual-specific, i.e. which are constant 
                         over alternatives. If neither opt.indiv and 
                         opt.alter are given, the model is estimated as 
                         if opt.indiv=1:r. Otherwise, the default is 
                         empty. 
                         
  opt.alter              indices of columns of x (=variables) which are 
                         alternative-specific, i.e. which vary over 
                         the alternatives (and eventually individuals). 
                         x[,opt.alter] should have a multiple of m 
                         columns, i.e. contain subsequent realizations 
                         for each of the alternatives. The default is empty. 
                         
 Output:

  myfit                  list with the components b, bv, and stat: 
                         
  b.indiv                p x m vector, estimated coefficients 
                         corresponding to individual-specific variables. 
                         The first column is zero. 
                         
  b.alter                q x 1 vector, estimated coefficients corresponding 
                         to alternative-specific variables. 
                         
  bv.indiv               (p*m) x (p*m) matrix, estimated covariance 
                         for b.indiv, matrix of p x p blocks. 
                         
  bv.alter               q x q matrix, estimated covariance for b.alter. 
                         
  bv.mixed               (p*m) x q matrix, estimated mixed covariances 
                         between b.alter and b.indiv, vector of p x q 
                         blocks. 
                         
  mu                     n x m vector, estimated response mu=P(y=j) 
                         corresponding to alternatives 1 ... m of y. 
                         
  stat                   list with the following statistics: 
                         
  stat.serror            standard errors, list containing components 
                         indiv and/or alter, respectively. 
                         
  stat.tvalues           t-values, list containing components 
                         indiv and/or alter, respectively. 
                         
  stat.pvalues           p-values, list containing components 
                         indiv and/or alter, respectively. 
                         
  stat.deviance          deviance, 
                         
  stat.loglik            log-likelihood, 
                         
  stat.r2                (pseudo) R^2. 
                         
  stat.adr2              adjusted (pseudo) R^2. 
                         
  stat.it                scalar, number of iterations needed 
                         
  stat.ret               scalar, return code: 
                         0 o.k., 
                         1 maximal number of iterations reached, 
                         -1 missing values have been encountered. 
                         
--------------------------------------------------------------
(C) MD*TECH Method and Data Technologies, 17.8.2000
