Article
Mathematics
Giacomo Aletti, Irene Crimaldi
Summary: In recent papers, the authors introduce, study, and apply a variant of the Eggenberger-Polya urn, called the rescaled Polya urn, which exhibits a reinforcement mechanism based on the last observations, persistent random fluctuation of the predictive mean, and convergence of the empirical mean to a deterministic limit. Motivated by empirical evidence, the authors demonstrate that the multidimensional Wright-Fisher diffusion with mutation can be obtained as a suitable limit of the predictive means associated with a family of rescaled Polya urns.
Article
Computer Science, Information Systems
Junji Jiang, Likang Wu, Hongke Zhao, Hengshu Zhu, Wei Zhang
Summary: Stock movement forecasting is often treated as a sequence prediction task using time series data. While deep learning models have been increasingly employed for fitting dynamic stock time series, few of them have focused on understanding the internal dynamics of the market system. To address this, the proposed HMM-ALSTM framework integrates the Hidden Markov Model (HMM) into the deep learning process, allowing for the discovery of hidden states and patterns that contribute to the stock time series data.
INFORMATION PROCESSING & MANAGEMENT
(2023)
Article
Chemistry, Analytical
Ting Lin, Miao Wang, Min Yang, Xu Yang
Summary: This paper addresses the issues with commonly used methods in mining time series data by proposing a novel approach that utilizes Wasserstein distance and autoencoder to learn discrete features and hidden Markov model to learn continuous features. The two models are then stacked to create an ensemble model with lower computational complexity and comparable classification accuracy to state-of-the-art methods.
Article
Computer Science, Artificial Intelligence
Jinbo Li, Witold Pedrycz, Xianmin Wang, Peng Liu
Summary: This study introduces a fuzzy model based on Hidden Markov Model (HMM) for time series prediction. The model uses fuzzy rules to describe the relationship between input and output time series and employs HMM to capture the temporal behavior of multivariate time series. Experimental results show that the proposed model outperforms fuzzy rule-based models without involving HMMs.
Article
Biology
Camila Braeutigam, Matteo Smerlak
Summary: In this study, we analyze Muller's ratchet phenomenon using a modified diffusion equation to obtain improved estimates for the mean click time.
JOURNAL OF THEORETICAL BIOLOGY
(2022)
Article
Statistics & Probability
Guillaume Kon Kam King, Omiros Papaspiliopoulos, Matteo Ruggiero
Summary: This article discusses the conditions for exact inference of a class of hidden Markov models on general state spaces, using a certain type of dual process to represent distributions and functions of interest as finite mixtures or products. Practical algorithms are provided for recursively updating parameters and approximating mixtures, showing superior performance to particle filters in accuracy and computational efficiency.
ELECTRONIC JOURNAL OF STATISTICS
(2021)
Article
Biochemistry & Molecular Biology
Wenyang Lyu, Xiaoyang Dai, Mark Beaumont, Feng Yu, Zhangyi He
Summary: A new Bayesian framework is introduced to estimate the timing and strength of natural selection and gene migration simultaneously, improving our understanding of the evolution and persistence of organismal diversity. By correlating genetic evolution with changes in ecological context, drivers of natural selection and gene migration can be inferred, showing the utility of the method through simulations and application to ancient chicken samples.
MOLECULAR ECOLOGY RESOURCES
(2022)
Article
Biology
Martina Favero, Henrik Hult, Timo Koski
Summary: The paper explores the coupled Wright-Fisher diffusion model and its corresponding ancestral process, deriving a dual process to describe the coupled evolutionary dynamics.
JOURNAL OF MATHEMATICAL BIOLOGY
(2021)
Article
Biology
Robert C. Griffiths, Paul A. Jenkins
Summary: In this paper, a maximum likelihood estimator for the recombination rate is derived based on a continuously observed, multi-locus, Wright-Fisher diffusion of haplotype frequencies, complementing existing work for an estimator of selection. It is found that the estimator has unusual properties as the observed information matrix can explode in finite time, allowing for error-free learning of the recombination parameter. The robustness of the recombination estimator to the presence of selection is also demonstrated.
JOURNAL OF MATHEMATICAL BIOLOGY
(2023)
Article
Mathematics
Tao Li, Jinwen Ma
Summary: The mixture of Gaussian process functional regressions (GPFRs) assumes independent random processes with different temporal structures for generating time series or sample curves. However, in reality, these structures are randomly transferred from a long time scale. To address this limitation, we propose the hidden-Markov-based GPFR mixture model (HM-GPFR) that describes the curves using both fine- and coarse-level temporal structures. The model combines the Gaussian process at the fine level and the hidden Markov process at the coarse level, resulting in a random process with state switching dynamics. Additionally, a Bayesian-hidden-Markov-based GPFR mixture model (BHM-GPFR) is developed to enhance the robustness of the model by incorporating priori parameters. Experimental results show high prediction accuracy and interpretability.
Article
Multidisciplinary Sciences
Ha Yoon Song, Jae Ho Lee
Summary: With the advancement of geopositioning systems and mobile devices, much research is being conducted on geopositioning data. Map matching, a core preprocessing technique for trajectory data, is gaining attention, particularly the use of Hidden Markov Model (HMM) for map matching. However, the HMM model simplifies the dependency of time series data excessively, leading to incorrect matching results. In this research, a new algorithm called trendHMM map matching is proposed, which improves upon the assumptions of HMM by considering a wider range of dependencies and incorporating neighboring data.
Article
Engineering, Environmental
Guang Yang, Shenghui Fang, Wenbing Gong, Yaolong Zhao, Mengyu Ge
Summary: Time series land cover maps are important materials, but illogical transitions exist between different time phases. Limited ground truth evaluation cannot guide users well. A method based on joint probability is proposed to evaluate the reliability of time series land cover products.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2021)
Article
Agriculture, Dairy & Animal Science
Kosuke Sumi, Swe Zar Maw, Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, Yoichiro Horii
Summary: This study focused on utilizing behavioral activities of dairy cows before calving to predict the time of parturition, proposing an integrated approach combining video sequences and Hidden Markov Model for prediction. Experimental results showed promising potential in practical applications, with high frequency of posture changes playing a central role in accurately predicting calving time.
Article
Statistics & Probability
Abdullah Asilkalkan, Xuwen Zhu
Summary: In this paper, a hidden Markov model for modeling matrix-variate time series data is proposed, which demonstrates high accuracy and competitiveness in state classification.
Article
Geochemistry & Geophysics
Kareth M. Leon-Lopez, Florian Mouret, Henry Arguello, Jean-Yves Tourneret
Summary: This article introduces a framework for anomaly detection, localization, and classification in crop monitoring using satellite remote sensing data. The method utilizes hidden Markov models to detect and localize outliers at a parcel level, followed by classification using a supervised classifier. Experimental results on synthetic and real data show better detection rates and the ability to localize and characterize anomalies compared to standard methods.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Ecology
Ana Y. Morales-Arce, Parul Johri, Jeffrey D. Jensen
Summary: The study presents an analysis pipeline for inferring the distribution of fitness effects from viral populations, accounting for non-standard population dynamics. The approach is demonstrated through two illustrative applications and potential applications to virus evolution research are discussed.
Article
Genetics & Heredity
Susanna Sabin, Ana Y. Morales-Arce, Susanne P. Pfeifer, Jeffrey D. Jensen
Summary: This study compares the evolutionary dynamics of the recombining M. canettii with the nonrecombining M. tuberculosis complex using whole-genome sequencing data and population genomic models. The authors discuss differences in observed genomic diversity and highlight the potential mis-inference caused by neglecting common model violations.
G3-GENES GENOMES GENETICS
(2022)
Article
Genetics & Heredity
Parul Johri, Wolfgang Stephan, Jeffrey D. Jensen
Summary: This study raises concerns about recent publications in PLOS Genetics that argue for the statistical identifiability and pervasive evolutionary role of soft selective sweeps in Drosophila and HIV populations. The results highlight the dangers of fitting evolutionary models without considering competing models and the tendency to view positive selection as a foregone conclusion in certain research areas.
Review
Evolutionary Biology
Brian Charlesworth, Jeffrey D. Jensen
Summary: This article discusses the genetic, demographic, and selective forces that limit the observed levels of DNA sequence variation in natural populations, and highlights the potentially important role of population size change in this process.
GENOME BIOLOGY AND EVOLUTION
(2022)
Article
Evolutionary Biology
Parul Johri, Adam Eyre-Walker, Ryan N. Gutenkunst, Kirk E. Lohmueller, Jeffrey D. Jensen
Summary: This article discusses the challenges of disentangling the effects of natural selection and population history on genome-wide variation in population genetics. It highlights the theoretical and computational challenges that still need to be addressed, as well as the difficulties in dealing with model complexity and violations, and offers thoughts on potentially fruitful next steps.
GENOME BIOLOGY AND EVOLUTION
(2022)
Editorial Material
Biochemistry & Molecular Biology
Brian Charlesworth, Jeffrey D. Jensen
Summary: This article addresses recent claims regarding the importance of indirect selection, arguing that it is not a new or poorly studied phenomenon and that alternative explanations exist for the patterns described by the authors.
Article
Multidisciplinary Sciences
Nuno M. Silva, Susanne Kreutzer, Angelos Souleles, Sevasti Triantaphyllou, Kostas Kotsakis, Dushka Urem-Kotsou, Paul Halstead, Nikos Efstratiou, Stavros Kotsos, Georgia Karamitrou-Mentessidi, Fotini Adaktylou, Areti Chondroyianni-Metoki, Maria Pappa, Christina Ziota, Adamantios Sampson, Anastasia Papathanasiou, Karen Vitelli, Tracey Cullen, Nina Kyparissi-Apostolika, Andrea Zeeb Lanz, Joris Peters, Jeremy Rio, Daniel Wegmann, Joachim Burger, Mathias Currat, Christina Papageorgopoulou
Summary: This study investigates mitochondrial diversity in Neolithic Greece, finding genetic homogeneity in maternal line throughout the Neolithic but population discontinuity between Neolithic and present-day Greeks. Along the Danubian expansion axis, there is a substantial decrease in mobility and an increasing contribution of local hunter-gatherer to the gene-pool of farmers.
SCIENTIFIC REPORTS
(2022)
Review
Biodiversity Conservation
Anna F. Probert, Daniel Wegmann, Lara Volery, Tim Adriaens, Rigers Bakiu, Sandro Bertolino, Franz Essl, Eugenio Gervasini, Quentin Groom, Guillaume Latombe, Dragana Marisavljevic, John Mumford, Jan Pergl, Cristina Preda, Helen E. Roy, Riccardo Scalera, Heliana Teixeira, Elena Tricarico, Sonia Vanderhoeven, Sven Bacher
Summary: Community science (or citizen science) provides an opportunity to address research questions beyond traditional methods while engaging communities. This study focuses on community science projects related to alien species, identifying key research questions and uncertainties that arise during study design, data collection, statistical analysis, and communication stages. The study suggests methods to reduce uncertainties and offers guidance for project implementation.
BIOLOGICAL INVASIONS
(2022)
Article
Biodiversity Conservation
Liam Singer, Xenia Wietlisbach, Raffael Hickisch, Eva Maria Schoell, Christoph Leuenberger, Angela Van den Broek, Manon Desalme, Koen Driesen, Mari Lyly, Francesca Marucco, Miroslav Kutal, Nives Pagon, Cristian Remus Papp, Paraskevi Milioni, Remigijus Uzdras, Ilgvars Zihmanis, Fridolin Zimmermann, Katrina Marsden, Klaus Hacklaender, Jose Vicente Lopez-Bao, Sybille Klenzendorf, Daniel Wegmann
Summary: Wolf populations in Europe are increasing, leading to conflicts with livestock owners. A study compiled livestock damage data from 21 countries between 2018 and 2020, finding regional variations in the target species, damage density, seasonal distribution, and temporal trend. The area of cultivated habitats occupied by wolves, as well as husbandry practices and damage prevention, were identified as important factors influencing the incidents.
BIOLOGICAL CONSERVATION
(2023)
Editorial Material
Biochemistry & Molecular Biology
Daniel Wegmann, Raphael Eckel
Summary: Two new studies using ancient DNA reveal how two significant admixture events in the evolutionary history of Europeans changed their adaptive trajectories and facilitated rapid evolution.
Article
Multidisciplinary Sciences
Hirzi Luqman, Daniel Wegmann, Simone Fior, Alex Widmer
Summary: Quaternary climate fluctuations drove many species to shift their geographic ranges, in turn shaping their genetic structures. Recently, it has been argued that adaptation may have accompanied species range shifts via the sieving of genotypes during colonisation and establishment. Luqman et al.'s study on the genetic landscape of the carnation species Dianthus sylvestris during the Quaternary glacial cycles provides direct evidence of the interplay between migration and adaptation in shaping species responses to climate change. The study shows that adaptive responses emerged concomitantly with range shifts and expansions, and were driven by the sieving of adaptive alleles across space and time. This reveals the importance of understanding the spatial patterns of adaptive variation in species today.
NATURE COMMUNICATIONS
(2023)
Article
Genetics & Heredity
Fabian B. Freund, Elise Kerdoncuff, Sebastian Matuszewski, Marguerite Lapierre, Marcel Hildebrandt, Jeffrey Jensen, Luca Ferretti, Amaury Lambert, Timothy Sackton, Guillaume Achaz
Summary: The standard neutral model of molecular evolution has often been used as a reference for population genomics. However, our study shows that alternative genealogical models, such as multiple merger coalescent models, may provide a better fit to observed allele frequency data. This has important implications for population genomic studies and related fields.
Review
Microbiology
John W. Terbot, Parul Johri, Schuyler W. Liphardt, Vivak Soni, Susanne P. Pfeifer, Brandon S. Cooper, Jeffrey M. Good, Jeffrey D. Jensen
Summary: In the past 3 years, the SARS-CoV-2 virus has caused a global health crisis with multiple waves of spread. Genomic surveillance efforts have increased to track and anticipate the virus's evolution, resulting in a large number of patient isolates available in public databases. However, accurately quantifying the emergence of adaptive viral variants is challenging due to various co-occurring and interacting evolutionary processes. This study outlines the critical components of an evolutionary baseline model for SARS-CoV-2, including mutation rates, recombination rates, fitness effects, infection dynamics, and compartmentalization, and discusses the current understanding of these parameters. Recommendations for future clinical sampling, model construction, and statistical analysis are also provided.
Article
Ecology
Lara Volery, Margarida Vaz Fernandez, Daniel Wegmann, Sven Bacher
Summary: Biodiversity is declining rapidly due to human activities, and accurately quantifying and comparing their impacts is crucial. A new framework is presented that introduces fundamental principles of ecological impact quantification, including the quantification of interactions between multiple drivers. The framework addresses key questions in global change science and provides a method to compare impacts and management actions over time.
Article
Evolutionary Biology
John W. Terbot II, Brandon S. Cooper, Jeffrey M. Good, Jeffrey D. Jensen
Summary: This study develops a simulation framework to study the intrahost evolutionary dynamics of SARS-CoV-2 and establish a baseline model for improved virus data analysis. The study finds that the evolution of SARS-CoV-2 is influenced by severe infection bottlenecks, low levels of reproductive skew, and strongly deleterious mutations.
GENOME BIOLOGY AND EVOLUTION
(2023)