mkStochastic

<p>A vector, matrix or array to transform.</p>

<p>mkStochastic ensures that it is a stochastic vector, matrix or array.</p>

Provides a variety of original and flexible user-friendly
statistical latent variable models and unsupervised learning algorithms to
segment and represent time-series data (univariate or multivariate), and
more generally, longitudinal data, which include regime changes.
'samurais' is built upon the following packages, each of them is an
autonomous time-series segmentation approach: Regression with Hidden
Logistic Process ('RHLP'), Hidden Markov Model Regression ('HMMR'),
Multivariate 'RHLP' ('MRHLP'), Multivariate 'HMMR' ('MHMMR'), Piece-Wise
regression ('PWR'). For the advantages/differences of each of them, the
user is referred to our mentioned paper references.

Florian Lecocq

samurais

mkStochastic: mkStochastic ensures that it is a stochastic vector, matrix or array.

Description

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Details