Difference between revisions of "GeneralizedIterativeScaling"
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This is one of the earliest [[category::method]]s used for inference in log-linear models. Though more sophisticated and faster methods have evolved, this [[category::method]] provides an insight in log linear models. | This is one of the earliest [[category::method]]s used for inference in log-linear models. Though more sophisticated and faster methods have evolved, this [[category::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 | ||
| + | |||
| + | <math> | ||
| + | p_i = \pi_i \mu \prod_{s=1}^d \mu_s^{b_{si}} | ||
| + | </math> | ||
| + | |||
| + | satisfying the constraints | ||
| + | |||
| + | <math> | ||
| + | \sum_{i \in I} b_{si}p_i = k_s | ||
| + | </math> | ||
Revision as of 10:42, 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
