bestDist {ExtDist} | R Documentation |

## Finding the best distribution for a (weighted) sample.

### Description

This function chooses the best fitted distribution, based on a specified criterion.

### Usage

```
bestDist(
X,
w = rep(1, length(X))/length(X),
candDist = c("Beta_ab", "Laplace", "Normal"),
criterion = c("AICc", "logLik", "AIC", "BIC", "MDL")
)
```

### Arguments

`X` |
Sample observations. |

`w` |
An optional vector of sample weights. |

`candDist` |
A vector of candidate distributions. |

`criterion` |
The basis on which the best fitted distribution is chosen. |

### Details

When comparing models fitted by maximum likelihood to the same data, the smaller the AIC, BIC or MDL, the better the fit. When comparing models using the log-likelihood criterion, the larger the log-likelihood the better the fit.

### Value

An object of class character containing the name of the best distribution and its corresponding parameter estimates.

### Note

The MDL criterion only works for parameter estimation by numerical maximum likelihood.

### Author(s)

Haizhen Wu and A. Jonathan R. Godfrey.

### Examples

```
X <- rBeta_ab(30, a = 0, b = 1, shape1 = 2, shape2 = 10)
# Determining the best distribution from the list of candidate distributions for the data X
Best.Dist <- bestDist(X, candDist = c("Laplace","Normal","Beta_ab"), criterion = "logLik")
# Printing the parameter estimates of the best distribution
attributes(Best.Dist)$best.dist.par
```

[Package

*ExtDist*version 0.7-2 Index]