 Usage:  {wg,b,sk,sdv,skl,slv,lk,iter} = dpls(w,d,dy,dl,y,lag,genau)  
 
 Input:

  w                      a matrix with start weights same dimensions as dy 
                         
  d                      a kxk matrix with inner unlagged designs (0 or 1) 
                         no diagonal values allowed 
                         
  dy                     a lxk matrix with outer designs (0 or 1) 
                         rows are counting manifest variables 
                         
  dl                     a kxk matrix with inner lagged designs (0 or 1) 
                         diagonal elements are showing autoregression 
                         
  y                      a nxl matrix with manifest variables (indicators) 
                         
  lag                    a scalar of lag order 
                         
  genau                  a scalar with canceling criterion 
                         
 Output:

  wg                     a matrix with weights 
                         
  b                      a matrix with loadings 
                         
  sk                     a matrix with path coefficients with dimensions 
                         like d (kxk) 
                         
  sdv                    a matrix with standarddeviations of path 
                         coefficients with dimensions like d (kxk) 
                         
  skl                    a matrix with lagged path coefficients with 
                         dimensions like d (kxk) and ordered like designed 
                         
  slv                    a matrix with standarddeviations of path 
                         coefficients with dimensions like d (kxk) 
                         
  lk                     a matrix with latent variables 
                         
  iter                   a scalar shows how many iterations used 
                         
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(C) MD*TECH Method and Data Technologies, 17.8.2000
