Propositionalisation of multiple sequence alignments using probabilistic models [PDF]
, 2008 Multiple sequence alignments play a central role in Bioinformatics. Most alignment representations are designed to facilitate knowledge extraction by human experts.
Holmes, Geoffrey +2 more
core +2 more sources
Clustering of Longitudinal Data: A Tutorial on a Variety of Approaches
Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 1, February 2026.ABSTRACT During the past two decades, methods for identifying groups with different trends in longitudinal data involving a single numeric outcome have become of increasing interest across many areas of research. To support researchers, we summarize the guidance from literature regarding the clustering of such data.
N. G. P. Den Teuling +2 more
wiley +1 more source
Measuring the Influence of Observations in HMMs through the Kullback-Leibler Distance
, 2012 We measure the influence of individual observations on the sequence of the hidden states of the Hidden Markov Model (HMM) by means of the Kullback-Leibler distance (KLD).
Nuel, Gregory, Perduca, Vittorio
core +1 more source
Portfolio Optimization for Pension Purposes: Literature Review
Journal of Economic Surveys, Volume 40, Issue 1, Page 45-72, February 2026.ABSTRACT This systematic review identifies persistent challenges and gaps in the literature on pension portfolio optimization models. We searched, selected, and critically analyzed 82 articles from three major academic databases published over the past decade to investigate the barriers to the effective implementation of these models.
Leonardo Moreira +2 more
wiley +1 more source
Online Health Management for Complex Nonlinear Systems Based on Hidden Semi‐Markov Model Using Sequential Monte Carlo Methods [PDF]
, 2012 Qinming Liu, Ming Dong
openalex +1 more source
Localizing the latent structure canonical uncertainty: Entropy profiles for hidden Markov models [PDF]
, 2007 Ce rapport concerne l'inférence sur les états de modèles de Markov cachés. Ces modèles se fondent sur des états non observés, qui ont en général une interprétation, dans le contexte d'une application donnée. Ceci rend nécessaire la conception d'outils de
Durand, Jean-Baptiste, Guédon, Yann
core
A Hidden Semi-Markov Model based approach for rehabilitation exercise assessment
Journal of Biomedical Informatics, 2018 In this paper, a Hidden Semi-Markov Model (HSMM) based approach is proposed to evaluate and monitor body motion during a rehabilitation training program. The approach extracts clinically relevant motion features from skeleton joint trajectories, acquired by the RGB-D camera, and provides a score for the subject's performance.
Capecci, Marianna +8 more
openaire +4 more sources
A Novel Method for ECG-Free Heart Sound Segmentation in Patients with Severe Aortic Valve Disease
SensorsSevere aortic valve diseases (AVD) cause changes in heart sounds, making phonocardiogram (PCG) analyses challenging. This study presents a novel method for segmenting heart sounds without relying on an electrocardiogram (ECG), specifically targeting ...
Elza Abdessater +7 more
doaj +1 more source
Nonhomogeneous hidden semi-Markov models for toroidal data
Journal of the Royal Statistical Society Series C: Applied StatisticsAbstract A nonhomogeneous hidden semi-Markov model is proposed to segment bivariate time series of wind and wave directions according to a finite number of latent regimes and, simultaneously, estimate the influence of time-varying covariates on the process’ survival under each regime.
Francesco Lagona, Marco Mingione
openaire +4 more sources
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models
, 2020 Ajay Kumar Tanwani +7 more
openalex +2 more sources