Compute goodness of fit as described in `AIC`

. The number of
parameters used correspond to the number of variables free to vary in the
general model.

goodness.of.fit(theta, u, method = c("AIC", "BIC"), k = 2)

## Arguments

theta |
A `list` of parameters as defined in `rtheta` .
For t this function, it will usually be the output of
`fit.full.GMCM` . |

u |
An `n` by `d` matrix of marginally uniform observations.
Rows corresponds to observations and columns to the dimensions of the
variables. I.e. these are often ranked and scaled test statistics or other
observations. |

method |
A `character` of length 1 which specifies the goodness of
fit to compute. Default is "AIC". "BIC" is also a option. |

k |
A integer specifying the default used constant "k" in AIC. See
`AIC` . |

## Value

A single number giving the goodness of fit as requested.

## Examples

#> iter 10 value -110.257470
#> iter 20 value -110.738198
#> final value -110.874731
#> converged

goodness.of.fit(theta1, u) # AIC

#> [1] -205.7495

goodness.of.fit(theta1, u, method = "BIC")

#> [1] -172.0326