Package classifiers :: Module multivariance

Module multivariance

Functions

meanvar(dataset, N, modelchoice=<class gmisclib.multivariance_q.quadratic at 0x2512290>)
Given a dataset, this produces a bunch of MCMC estimates of plausible means and inverse covariance matrices for the dataset.

source code

test_quadratic()

source code

test_diag_quadratic()

source code

test_multimu()

source code

test_multimu_diag()

source code

Variables
	ERGCOVER = `3.0`
	HUGE = `1e+30`
	FromName = `{'quadratic': MQ.quadratic, 'diag_quadratic': MQ.di...`
	__package__ = `'classifiers'`

Imports: Num, mcmc, die, mcmc_helper, MC, MQ, MM

Function Details

meanvar(dataset, N, modelchoice=<class gmisclib.multivariance_q.quadratic at 0x2512290>)

source code

Given a dataset, this produces a bunch of MCMC estimates of plausible means and inverse covariance matrices for the dataset. Modelchoice is a particular size model, e.g. an instance of quadratic. The output is in the form [ (mean, inv_covar), ... ].

Variables Details

FromName

Value:

{'quadratic': MQ.quadratic, 'diag_quadratic': MQ.diag_quadratic, 'mult
i_mu': MM.multi_mu, 'multi_mu_diag': MM.multi_mu_diag}