 Usage:  {filtX,KG,PreviousPs,clipInd} = rICfil(y,mu,Sig,H,F,Q,R,cliptyp,A,b)  
 
 Input:

  y                      T x m matrix of observed time series, 
                         T is the number of observations, 
                         m is the dimension of time series 
                         
  mu                     n x 1 vector, the mean of the initial state 
                         
  Sig                    n x n covariance matrix of the initial state 
                         
  H                      m x n matrix 
                         
  F                      n x n matrix 
                         
  Q                      m x m variance-covariance matrix 
                         
  R                      n x n variance-covariance matrix 
                         
  cliptyp                numeric : either 0 for simultaneous clipping 
                         1 for separate clipping (AO) 
                         2 for separate clipping (IO) 
                         
  As                     T,n,n matrix, "vector" of Lagrange-Matrices A; are to be produced by calibrIC 
                         or n,n matrix, uniform Lagrange-Matrix A 
                         
  bs                     T vector, the clipping heights; are to be produced by calibrIC 
                         or numerical (uniform) clipping height 
                         
 Output:

  filtX                  T x n matrix of filtered time series 
                         
  KG                     T x n x m "vector" of Kalman-Gain-matrices for different times 
                         
  PreviousPs             T x n x n "vector" of P_t|t's 
                         
  clippInd               T vector of 1 (if rlsfil clipped at instance t) and 0 (else) 
                         
--------------------------------------------------------------
(C) MD*TECH Method and Data Technologies, 17.8.2000
