 Usage:  {ll1,ll2} = glmlld(code,eta,y{,opt})  

 

 Input:



  code                   text string, the short code for the model (e.g. 

                         "bipro" for probit or "noid" for linear model). 

                         Append "fs" to the code for the expected ll2 

                         instead of ll2 (-> Fisher scoring algorithm). 

                         

  eta                    n x d matrix, the index values. 

                         

  y                      n x d matrix, the response values. 

                         

  opt                    optional, a list with optional input. The macro 

                         "glmopt" can be used to set up this parameter. 

                         

  opt.pow                scalar, power for power link. If not given, set 

                         to 0 (logarithm). 

                         

  opt.nbk                scalar, extra parameter k for negative binomial 

                         distribution. If not given, set to 1 (geometric 

                         distribution). 

                         

 Output:



  ll1                    n x d matrix, 1st derivative of log-likelihood. 

                         

  ll2                    n x d matrix, 2nd derivative of log-likelihood. 

                         

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(C) MD*TECH Method and Data Technologies, 21.9.2000

