statsmodels.multivariate.factor.Factor.fit

Factor.fit(maxiter=50, tol=1e-08, start=None, opt_method='BFGS', opt=None, em_iter=3, rng=None)

Estimate factor model parameters.

Parameters:

maxiterint

Maximum number of iterations for iterative estimation algorithms

tolfloat

Stopping criteria (error tolerance) for iterative estimation algorithms

startarray_like

Starting values, currently only used for ML estimation

opt_methodstr

Optimization method for ML estimation

optdict-like

Keyword arguments passed to optimizer, only used for ML estimation

em_iterint

The number of EM iterations before starting gradient optimization, only used for ML estimation.

rng{None, int, array_like[int], numpy.random.Generator, numpy.random.RandomState}, optional

If rng is None, a new Generator is created using fresh entropy from the operating system. If rng is an int or array of ints, a new Generator is created, seeded with rng. If rng is already a Generator or RandomState instance, that instance is used. Only used for ML estimation to generate starting values when start is None.

Returns:

FactorResults

Results class instance.