mosaicperm.factor.MosaicBCV¶

class mosaicperm.factor.MosaicBCV(new_exposures: array, *args, **kwargs)[source]¶

Mosaic factor test based on mosaicperm.statistics.adaptive_mosaic_bcv_stat()

Parameters:

outcomesnp.array: (n_obs, n_subjects) array of outcomes, e.g., asset returns. outcomes may contain nans to indicate missing values.
exposuresnp.array: (n_obs, n_subjects, n_factors) array of factor exposures OR (n_subjects, n_factors) array of factor exposures if the exposures do not change with time.
new_exposuresnp.array or list: (n_models, n_subject)-shaped array such that new_exposures[i] is an array of new exposures.
tilesmosaicperm.tilings.Tiling: An optional Tiling to use as the tiling.
**kwargsdict: Optional kwargs to default_factor_tiles(). Ignored if tiles is provided.

Examples

>>> import numpy as np
>>> import mosaicperm as mp
>>> 
>>> # synthetic outcomes and exposures
>>> n_obs, n_subjects, n_factors = 100, 200, 20
>>> outcomes = np.random.randn(n_obs, n_subjects)
>>> exposures = np.random.randn(n_obs, n_subjects, n_factors)
>>> 
>>> # estimate candidate exposures on the first half of the data
>>> n0 = int(0.5 * n_obs)
>>> resid0 = mp.factor.ols_residuals(outcomes[0:n0], exposures[0:n0])
>>> new_exposures = mp.statistics.approximate_sparse_pcas(np.corrcoef(resid0.T))
>>> 
>>> # fit mosaic permutation test
>>> mpt_bcv = mp.factor.MosaicFactorTest(
...     outcomes=outcomes[n0:],
...     exposures=exposures[n0:],
...     new_exposures=new_exposures,
>>> )
>>> mpt_bcv.fit().summary()

Methods

`compute_mosaic_residuals`()	Computes mosaic-style residual estimates.
`fit`([nrand, verbose])	Runs the mosaic permutation test.
`fit_tseries`([nrand, verbose, n_timepoints, ...])	Runs mosaic permutation tests for various windows of the data, producing a time series of p-values.
`permute_residuals`([method])	Permutes residuals within tiles.
`plot_tseries`([time_index, alpha, show_plot])	Plots the results of `fit_tseries()`.
`summary`(args, *kwargs)	Produces an output summarizing the test.
`summary_plot`([show_plot])	Produces a plot summarizing the results of the test.