ltr_reg_clus

A left to right initial linear regression clustering method using the
coefficient differences and Hotelling's T-squared test

Develops algorithms for fitting, prediction, simulation
and initialization of the following models
(1)- hidden hybrid Markov/semi-Markov model,
introduced by Guedon (2005) <doi:10.1016/j.csda.2004.05.033>,
(2)- nonparametric mixture of B-splines emissions (Langrock et al., 2015
<doi:10.1111/biom.12282>),
(3)- regime switching regression model
(Kim et al., 2008 <doi:10.1016/j.jeconom.2007.10.002>) and auto-regressive
hidden hybrid Markov/semi-Markov model,
(4)- spline-based nonparametric
estimation of additive state-switching models
(Langrock et al., 2018 <doi:10.1111/stan.12133>)
(5)- robust emission model proposed by
Qin et al, 2024 <doi:10.1007/s10479-024-05989-4>
(6)- several emission distributions, including mixture of multivariate normal
(which can also handle missing data using EM algorithm) and multi-nomial emission
(for modeling polymer or DNA sequences)
(7)- tools for prediction of future state sequence, computing the score of a new sequence,
splitting the samples and sequences to train and test sets, computing the information measures of
the models, computing the residual useful lifetime (reliability) and many other useful tools ...
(read for more description: Amini et al., 2022 <doi:10.1007/s00180-022-01248-x> and its
arxiv version: <doi:10.48550/arXiv.2109.12489>).

Morteza Amini

hhsmm

Hidden Hybrid Markov/Semi-Markov Model Fitting

Afarin Bayat

Reza Salehian

ltr_reg_clus function

<dl><dt>Dat</dt>
<dd>a data matrix</dd>
<dt>k</dt>
<dd>number of clusters</dd>
<dt>resp.ind</dt>
<dd>the column indices of the response variables for the linear regression clustering approach. The
default is 1, which means that the first column is the univariate response variable</dd></dl>

Arguments

Morteza Amini, <a href="/link/morteza.amini%40ut.ac.ir?package=hhsmm&version=0.4.2" data-mini-rdoc="hhsmm::morteza.amini@ut.ac.ir">morteza.amini@ut.ac.ir</a>

Author

left to right linear regression clustering — ltr_reg_clus

<dl>

<dt>Dat</dt>
<dd>a data matrix</dd>


<dt>k</dt>
<dd>number of clusters</dd>


<dt>resp.ind</dt>
<dd>the column indices of the response variables for the linear regression clustering approach. The
default is 1, which means that the first column is the univariate response variable</dd>

</dl>

Morteza Amini, <a href='mailto:morteza.amini@ut.ac.ir'>morteza.amini@ut.ac.ir</a>

ltr_reg_clus: left to right linear regression clustering

Description

Usage

Value

Arguments

Author