scholarly journals Bayesian hidden Markov modelling using circular-linear general projected normal distribution

2015 ◽  
Vol 26 (2) ◽  
pp. 145-158 ◽  
Author(s):  
Gianluca Mastrantonio ◽  
Antonello Maruotti ◽  
Giovanna Jona-Lasinio
Keyword(s):  
Normal Distribution ◽  
Hidden Markov ◽  
Markov Modelling ◽  
Projected Normal Distribution

A Bayesian regression model for circular data based on the projected normal distribution

2011 ◽  
Vol 11 (3) ◽  
pp. 185-201 ◽  
Author(s):  
Gabriel Nuñez-Antonio ◽  
Eduardo Gutiérrez-Peña ◽  
Gabriel Escarela
Keyword(s):  
Regression Model ◽  
Normal Distribution ◽  
Bayesian Regression ◽  
Circular Data ◽  
Projected Normal Distribution

Hidden Markov Modelling Techniques for Haplotype Analysis

2004 ◽  
pp. 37-52 ◽  
Author(s):  
Mikko Koivisto ◽  
Teemu Kivioja ◽  
Heikki Mannila ◽  
Pasi Rastas ◽  
Esko Ukkonen
Keyword(s):  
Haplotype Analysis ◽  
Hidden Markov ◽  
Markov Modelling ◽  
Modelling Techniques

scholarly journals An application of upscaled optimal foraging theory using hidden Markov modelling: year-round behavioural variation in a large arctic herbivore

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Larissa T. Beumer ◽  
Jennifer Pohle ◽  
Niels M. Schmidt ◽  
Marianna Chimienti ◽  
Jean-Pierre Desforges ◽  
...  
Keyword(s):  
Optimal Foraging ◽  
Hidden Markov ◽  
Optimal Foraging Theory ◽  
Foraging Theory ◽  
Markov Modelling

scholarly journals Continuous-index hidden Markov modelling of array CGH copy number data

2007 ◽  
Vol 23 (8) ◽  
pp. 1006-1014 ◽  
Author(s):  
Susann Stjernqvist ◽  
Tobias Rydén ◽  
Martin Sköld ◽  
Johan Staaf
Keyword(s):  
Copy Number ◽  
Array Cgh ◽  
Hidden Markov ◽  
Copy Number Data ◽  
Markov Modelling ◽  
Continuous Index

ACOUSTIC-PHONETIC DECODING OF SPANISH CONTINUOUS SPEECH

1994 ◽  
Vol 08 (01) ◽  
pp. 155-180 ◽  
Author(s):  
I. GALIANO ◽  
E. SANCHIS ◽  
F. CASACUBERTA ◽  
I. TORRES
Keyword(s):  
Markov Models ◽  
Hidden Markov ◽  
Recognition Rate ◽  
Grammatical Inference ◽  
Mathematical Framework ◽  
Markov Modelling ◽  
Unit Model ◽  
Training Samples ◽  
Speech Corpora ◽  
Selection Of

The design of current acoustic-phonetic decoders for a specific language involves the selection of an adequate set of sublexical units, and a choice of the mathematical framework for modelling the corresponding units. In this work, the baseline chosen for continuous Spanish speech consists of 23 sublexical units that roughly correspond to the 24 Spanish phonemes. The process of selection of such a baseline was based on language phonetic criteria and some experiments with an available speech corpora. On the other hand, two types of models were chosen for this work, conventional Hidden Markov Models and Inferred Stochastic Regular Grammars. With these two choices we could compare classical Hidden Markov modelling where the structure of a unit-model is deductively supplied, with Grammatical Inference modelling where the baseforms of model-units are automatically generated from training samples. The best speaker-independent phone recognition rate was 64% for the first type of modelling, and 66% for the second type.

scholarly journals Estimating the contribution of HIV-infected adults to household pneumococcal transmission in South Africa, 2016–2018: A hidden Markov modelling study

2021 ◽  
Vol 17 (12) ◽  
pp. e1009680
Author(s):  
Deus Thindwa ◽  
Nicole Wolter ◽  
Amy Pinsent ◽  
Maimuna Carrim ◽  
John Ojal ◽  
...  
Keyword(s):  
South African ◽  
Hidden Markov ◽  
Age Groups ◽  
Hiv Status ◽  
Older Children ◽  
Markov Modelling ◽  
Household Transmission ◽  
Pneumococcal Carriage ◽  
Immunodeficiency Virus ◽  
Infected Adult

Human immunodeficiency virus (HIV) infected adults are at a higher risk of pneumococcal colonisation and disease, even while receiving antiretroviral therapy (ART). To help evaluate potential indirect effects of vaccination of HIV-infected adults, we assessed whether HIV-infected adults disproportionately contribute to household transmission of pneumococci. We constructed a hidden Markov model to capture the dynamics of pneumococcal carriage acquisition and clearance observed during a longitudinal household-based nasopharyngeal swabbing study, while accounting for sample misclassifications. Households were followed-up twice weekly for approximately 10 months each year during a three-year study period for nasopharyngeal carriage detection via real-time PCR. We estimated the effect of participant’s age, HIV status, presence of a HIV-infected adult within the household and other covariates on pneumococcal acquisition and clearance probabilities. Of 1,684 individuals enrolled, 279 (16.6%) were younger children (<5 years-old) of whom 4 (1.5%) were HIV-infected and 726 (43.1%) were adults (≥18 years-old) of whom 214 (30.4%) were HIV-infected, most (173, 81.2%) with high CD4+ count. The observed range of pneumococcal carriage prevalence across visits was substantially higher in younger children (56.9–80.5%) than older children (5–17 years-old) (31.7–50.0%) or adults (11.5–23.5%). We estimate that 14.4% (95% Confidence Interval [CI]: 13.7–15.0) of pneumococcal-negative swabs were false negatives. Daily carriage acquisition probabilities among HIV-uninfected younger children were similar in households with and without HIV-infected adults (hazard ratio: 0.95, 95%CI: 0.91–1.01). Longer average carriage duration (11.4 days, 95%CI: 10.2–12.8 vs 6.0 days, 95%CI: 5.6–6.3) and higher median carriage density (622 genome equivalents per millilitre, 95%CI: 507–714 vs 389, 95%CI: 311.1–435.5) were estimated in HIV-infected vs HIV-uninfected adults. The use of ART and antibiotics substantially reduced carriage duration in all age groups, and acquisition rates increased with household size. Although South African HIV-infected adults on ART have longer carriage duration and density than their HIV-uninfected counterparts, they show similar patterns of pneumococcal acquisition and onward transmission.

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