lnre.goodness.of.fit {UCS} | R Documentation |

## Perform Goodness-of-Fit Evaluation of LNRE Model

### Description

Evaluate the goodness-of-fit of a LNRE model with a
multivariate chi-squared test (Baayen, 2001, Sec. 3.3).

### Usage

lnre.goodness.of.fit(model, m.max=15)

### Arguments

`model` |
an object representing a LNRE model whose parameters have
been estimated from observed word frequency data. Currently, the
Zipf-Mandelbrot (ZM, class `"zm"` ) and the finite
Zipf-Mandelbrot (fZM, class `"fzm"` ) models are
supported. |

`m.max` |
highest frequency rank to be included in the evaluation
(limited by the number of ranks stored in the `model` object). |

### Details

This function performs a multivariate chi-squared test to evaluate the
goodness-of-fit of an LNRE model (Baayen 2001, p. 119-122).

All LNRE models that follow the UCS/R conventions are supported.
In particular, they must specify the number of parameters estimated
from the observed data (in the `n.param`

component), and they
must provide appropriate implementations of the `EV`

, `EVm`

,
and `VV`

methods. Currently available LNRE models are objects of class
`"zm"`

or `"fzm"`

. The `model`

object must include observed
frequency data (in components `N`

, `V`

, and `spc`

),
which is usually achieved by estimating the model parameters from the
observed frequency spectrum.

### Value

A data frame with one row and three columns:

`X2` |
the value of the multi-variate *χ^2* test statistic |

`df` |
the degrees of freedom of the approximate *χ^2*
distribution of the test statistic under the null hypothesis |

`p` |
the p-value for the test |

### References

Baayen, R. Harald (2001). *Word Frequency Distributions.* Kluwer,
Dordrecht.

### See Also

`zm`

, `fzm`

[Package

*UCS* version 0.5

Index]