Difference between revisions of "GeneralizedIterativeScaling"

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<math>
 
<math>
p_i = \pi_i \mu \prod_{s=1}^d \mu_s^{b_{si}}
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(1) \quad \quad p_i = \pi_i \mu \prod_{s=1}^d \mu_s^{b_{si}}  
 
</math>
 
</math>
  
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<math>
 
<math>
\sum_{i \in I} b_{si}p_i = k_s
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(2) \quad \quad \sum_{i \in I} b_{si}p_i = k_s  
 
</math>
 
</math>
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 +
== Existence of a solution ==

Revision as of 09:46, 27 September 2011

This is one of the earliest methods used for inference in log-linear models. Though more sophisticated and faster methods have evolved, this method provides an insight in log linear models.

What problem does it address

The objective of this method is to find a probability function of the form

satisfying the constraints

Existence of a solution