Local Empirical Bayes
Empirical Bayes estimators consider the "real" rate associated with each
area is not known,
and that observed rate
is available. The idea of Bayesian estimators is assumed that the actual rate is a random variable having a mean and a known variance.
The best
estimator in this rate
is a linear combination of the observed rate
(events / population) in area A
and an average value B
weighted by a factor C.
The average weight may be used in the average rate of the surrounding areas, in this case, the method is called Local Empirical Bayes.
It is
accessible through:
Plugins > Spatial Analysis > Local Empirical Bayes...
This
interface consists of the
following steps:
1.
Input Information:
- Layer Name: Select the
desired Layer.
- Load GPM: Loads a gpm
from file, if not, creates a new one.
- Attribute Link:
Defines the attribute that identifies the objects of this layer.
- GPM: Opens a dialog
to select a file with a desired proximity matrix.
2.
Operation Parameters:
- Event Attr Name:
Attribute name that identifies the desired event information.
- Population Attr Name: Attribute
name that identifies the population information.
- Rate Correction: This
is the multiplicative rate correction value.
3. Output
Information:
- Repository: Defines
where the output data will be saved.
- Layer Name: Defines the
name to create the output layer.
Click OK and then the local
bayes rate will be calculated.
Note: To calculate
Bayesian Rates, the denominator (population at risk) does not have
values equal or smaller than zero.