Changeset 290 for doc/tutorial

Timestamp:

03/06/09 15:03:45 (16 years ago)

Author:

smidl

Message:

correction of ARX tutorial

Files:

• doc/tutorial/tut_arx.dox (modified) (1 diff)

doc/tutorial/tut_arx.dox

@@ -30 +30 @@
 For online estimation with stationary parameters can be easily achieved by collecting the sufficient statistics described above recursively.
 
-Extension to non-stationaly parameters, \f$ \theta_t , r_t \f$ can be achieved by operation called forgetting. This is an approximation of Bayesian filtering see [Kulhavy]. The resulting algorithm is defined by manipulation of sfficient statistics:
+Extension to non-stationaly parameters, \f$ \theta_t , r_t \f$ can be achieved by operation called forgetting. This is an approximation of Bayesian filtering see [Kulhavy]. The resulting algorithm is defined by manipulation of sufficient statistics:
 <dl>
 <dt>Information matrix</dt> <dd>which is a sum of outer products \f[ 
-V_t = V_{t-1} + \phi \left[\begin{array}{c}y_{t}\\ \psi_{t}\end{array}\right]
+V_t = \phi V_{t-1} +  \left[\begin{array}{c}y_{t}\\ \psi_{t}\end{array}\right]
 \begin{array}{c} [y_{t}',\,\psi_{t}']\\ \\\end{array}
 +(1-\phi) V_0
 \f]</dd>
 <dt>"Degree of freedom"</dd>  <dd>which is an accumulator of number of data records \f[
-\nu_t = \nu_{t-1} + \phi + (1-\phi) \nu_0
+\nu_t = \phi \nu_{t-1} + 1 + (1-\phi) \nu_0
 \f]</dd>
 </dl>