Results 21 to 30 of about 7,474,817 (334)
momentuHMM: R package for generalized hidden Markov models of animal movement [PDF]
, 2017 Discrete‐time hidden Markov models (HMMs) have become an immensely popular tool for inferring latent animal behaviours from telemetry data. While movement HMMs typically rely solely on location data (e.g.
B. McClintock, T. Michelot
semanticscholar +1 more source
SOLUTION TO EVALUATION PROBLEM OF HIDDEN SEMI-MARKOV QP-MODELS
Advanced Engineering Research, 2014 A hidden semi-Markov QP-model is considered; and the way it could be embedded in a general hidden semi-Markov model is shown. The estimation problem (the first of three classical theory problems of the hidden Markov models and hidden semi-Markov models ...
V. M. Deundyak, M. A. Zhdanova
doaj +1 more source
Conference on Empirical Methods in Natural Language Processing, 2002 We describe new algorithms for training tagging models, as an alternative to maximum-entropy models or conditional random fields (CRFs). The algorithms rely on Viterbi decoding of training examples, combined with simple additive updates.
M. Collins
semanticscholar +1 more source
Generalized Hidden Markov Models for Phylogenetic Comparative Datasets
bioRxiv, 2020 Hidden Markov models (HMM) have emerged as an important tool for understanding the evolution of characters that take on discrete states. Their flexibility and biological sensibility make them appealing for many phylogenetic comparative applications ...
James D Boyko, Jeremy M. Beaulieu
semanticscholar +1 more source
Supply Sequence Modelling Using Hidden Markov Models
Applied Sciences, 2022 Logistics processes, their effective planning as well as proper management and effective implementation are of key importance in an enterprise. This article analyzes the process of supplying raw materials necessary for the implementation of production ...
Anna Borucka +5 more
doaj +1 more source
Scalable Bayesian Inference for Coupled Hidden Markov and Semi-Markov Models
Journal of Computational And Graphical Statistics, 2019 Bayesian inference for coupled hidden Markov models frequently relies on data augmentation techniques for imputation of the hidden state processes. Considerable progress has been made on developing such techniques, mainly using Markov chain Monte Carlo ...
Panayiota Touloupou +2 more
semanticscholar +1 more source
Human Mutation, 2012 The rate at which nonsynonymous single nucleotide polymorphisms (nsSNPs) are being identified in the human genome is increasing dramatically owing to advances in whole‐genome/whole‐exome sequencing technologies.
Hashem A. Shihab +7 more
semanticscholar +1 more source
Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R [PDF]
Journal of Statistical Software, 2017 Sequence analysis is being more and more widely used for the analysis of social sequences and other multivariate categorical time series data. However, it is often complex to describe, visualize, and compare large sequence data, especially when there are
Satu Helske, Jouni Helske
semanticscholar +1 more source
EURASIP Journal on Audio, Speech, and Music Processing, 2010 Speaker identification performance is almost perfect in neutral talking environments. However, the performance is deteriorated significantly in shouted talking environments.
Ismail Shahin
doaj +1 more source
Hidden Markov models: the best models for forager movements? [PDF]
PLoS ONE, 2013 One major challenge in the emerging field of movement ecology is the inference of behavioural modes from movement patterns. This has been mainly addressed through Hidden Markov models (HMMs).
Rocio Joo +3 more
doaj +1 more source