Weights {demest} | R Documentation

## Specify priors for the weights in a Mix prior.

### Description

In normal usage, it is better to accept the default priors for the weights than to specify them explicitly. End users are therefore unlikely to need this function.

### Usage

    Weights(mean = 0, sd = 1, damp = Damp(), scale1 = HalfT(), scale2 = HalfT())

### Arguments

`mean` | The mean of the prior for `mean`. Defaults to 0.
`sd` | The standard deviation of the prior for `mean`. Defaults to 1.
`damp` | An object of class `Damp`.
`scale1` | An object of class `HalfT` defining the prior for `error1`.
`scale2` | An object of class `HalfT` defining the prior for `error2`.

### Details

A `Mix` prior treats an interaction as a mixture of normal distributions. The weights, also referred as mixture parameters, evolve over time. The evolution of the weight for each component is governed by an auto-regressive time series model. Specifically, transformed values of the weights are modelled using

`level1[k,h] = level2[k,h] + error1[k,h]`

`level2[k,h] = mean + damp * level2[k-1,h] + error2[k,h]`

`mean` has a normal prior.

`damp` has the boundary-avoiding prior described in Gelman et al (2004) p316-317. This prior is equivalent to assuming a Beta(2, 2) prior on the transformed parameter (`damp`+0.5)/2.

`error1` and `error2` both have half-t priors. These priors have the defaults described in `HalfT`.

### Value

An object of class `Weights`.

### See Also

Mixture priors are specified using `Mix`. The weights in a mixture prior are specified using `Weights`.

[Package demest version 0.0.0.3.1 Index]