# Calculate goodness of fit statistics for a naive discriminative learning model.

### Description

`ndlStatistics`

takes an Naive Discriminary Learning model
object as generated by `ndlClassify`

and calculates a
range of goodness of fit statistics using
`modelStatistics`

.

### Usage

1 |

### Arguments

`ndl` |
A naive discriminative learning model fitted with |

`...` |
Control arguments to be passed along to |

### Value

A list with the following components:

`n.data`

sum frequency of data points

`df.null`

degrees of freedom of the Null model

`df.model`

degrees of freedom of the fitted model

`statistics`

a list of various measures of goodness of fit calculated with

`modelStatistics`

### Author(s)

Antti Arppe and Harald Baayen

### References

Arppe, A. and Baayen, R. H. (in prep.) Statistical modeling and the principles of human learning.

### See Also

See also `ndlClassify`

, `modelStatistics`

.

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
data(think)
set.seed(314)
think <- think[sample(1:nrow(think),500),]
think.ndl <- ndlClassify(Lexeme ~ Agent + Patient, data=think)
ndlStatistics(think.ndl)
## Not run:
data(dative)
dative.ndl <- ndlClassify(RealizationOfRecipient ~ AnimacyOfRec + DefinOfRec +
PronomOfRec + AnimacyOfTheme + DefinOfTheme + PronomOfTheme, data=dative)
ndlStatistics(dative.ndl)
## End(Not run)
``` |