Mix {demest} | R Documentation

## Specify a Mix prior.

### Description

A `Mix` prior is used to model an iteraction that includes an "along" dimension (typically, but not necessarily, time), and additional dimensions. Values for the additional dimensions evolve, generally smoothly, across successive values of the "along" dimension. A typical application is modelling age-structures that change gradually over time.

### Usage

    Mix(
      along = NULL,
      components = Components(),
      weights = Weights(),
      covariates = NULL,
      error = Error(),
      maxComponents = 10
    )

### Arguments

`along` | Name of a dimension.
`components` | An object of class `Components`.
`weights` | An object of class `Weights`.
`covariates` | An object of class `Covariates` or `NULL` (the default). If `covariates` is `NULL`, the prior does not include covariates.
`error` | An object of class `Error`.
`maxComponents` | The maximum number of components. Defaults to 10.

### Details

The prior is modified from a model developed by Kunihama and Dunson (2013). The model is non-parametric, meaning that it extracts structure from the data with minimal guidance from the user. It is designed for use with sparse data.

### References

Kunihama, T and Dunson, DB. 2013. Bayesian modeling of temporal dependence in large sparse contingency tables. Journal of the American Statistical Association, 108(504): 1324-1338.

### See Also

Priors for the components can be specified using function `Components`, and weights (ie mixing parameters) can be specified using function `Weights`. However, in normal usage, it is typically best to stick with the defaults.

### Examples

    Mix()

[Package demest version 0.0.0.3.1 Index]