Iopt

class pyoptex.doe.fixed_structure.metric.Iopt(n=10000, cov=None, complete=True)

The I-optimality criterion. Computes the average (average) prediction variance if multiple Vinv are provided.

Attributes

covfunc(Y, X)

A function computing the covariate parameters and potential extra random effects.

momentsnp.array(2d)

The moments matrix.

samplesnp.array(2d)

The covariate expanded samples for the moments matrix.

nint

The number of samples.

__init__(n=10000, cov=None, complete=True)

Creates the metric

Parameters

nint

The number of samples to compute the moments matrix.

covfunc(Y, X)

The covariance function

completebool

Whether to only use the coordinates or completely randomly initialize the samples to generate the moments matrix.

Methods

Iopt.call(Y, X, params)	Computes the I-optimality criterion.
Iopt.init(Y, X, params)	Initializes the metric for each random initialization of the coordinate-exchange algorithm.
Iopt.preinit(params)	Pre-initializes the metric