Stochastic models of atmospheric clouds structure
Sign Up to like & getrecommendations! Published in 2018 at "Statistical Papers"
DOI: 10.1007/s00362-018-1036-7
Abstract: This paper deals with numerical simulation of random fields corresponding to a stochastic structure of atmospheric clouds. We construct numerical models to simulate the optical thickness of stratus clouds as well as indicator fields of… read more here.
Keywords: clouds structure; stochastic models; structure; atmospheric clouds ... See more keywords
Frames, Erasures, and Signal Estimation with Stochastic Models
Sign Up to like & getrecommendations! Published in 2019 at "Acta Applicandae Mathematicae"
DOI: 10.1007/s10440-019-00304-x
Abstract: Frame properties and conditions are determined that would minimize the error in signal reconstruction or estimation in the presence of noise and erasures. The special focus here is on stochastic models. These include estimating a… read more here.
Keywords: estimation; erasures signal; frames erasures; stochastic models ... See more keywords
Trajectory inference and parameter estimation in stochastic models with temporally aggregated data
Sign Up to like & getrecommendations! Published in 2018 at "Statistics and Computing"
DOI: 10.1007/s11222-017-9779-x
Abstract: Stochastic models are of fundamental importance in many scientific and engineering applications. For example, stochastic models provide valuable insights into the causes and consequences of intra-cellular fluctuations and inter-cellular heterogeneity in molecular biology. The chemical… read more here.
Keywords: temporally aggregated; estimation; aggregated data; model ... See more keywords
GPS-BDS-Galileo double-differenced stochastic model refinement based on least-squares variance component estimation
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Navigation"
DOI: 10.1017/s0373463321000564
Abstract: Abstract Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most… read more here.
Keywords: least squares; squares variance; based least; stochastic models ... See more keywords
Stochastic models of polymerization based axonal actin transport.
Sign Up to like & getrecommendations! Published in 2019 at "Physical biology"
DOI: 10.1088/1478-3975/ab29cd
Abstract: Recent advances in live cell imaging of F-actin structures, combined with pulse-chase imaging and computational modeling have suggested that actin is transported along the axon via biased polymerization of metastable actin fibers (actin trails). This… read more here.
Keywords: polymerization; actin; axonal actin; transport ... See more keywords
Evidence-based controls for epidemics using spatio-temporal stochastic models in a Bayesian framework
Sign Up to like & getrecommendations! Published in 2017 at "Journal of The Royal Society Interface"
DOI: 10.1098/rsif.2017.0386
Abstract: The control of highly infectious diseases of agricultural and plantation crops and livestock represents a key challenge in epidemiological and ecological modelling, with implemented control strategies often being controversial. Mathematical models, including the spatio-temporal stochastic… read more here.
Keywords: temporal stochastic; spatio temporal; control; stochastic models ... See more keywords
Infinite ergodic theory for three heterogeneous stochastic models with application to subrecoil laser cooling.
Sign Up to like & getrecommendations! Published in 2022 at "Physical review. E"
DOI: 10.1103/physreve.105.064126
Abstract: We compare ergodic properties of the kinetic energy for three stochastic models of subrecoil-laser-cooled gases. One model is based on a heterogeneous random walk (HRW), another is an HRW with long-range jumps (the exponential model),… read more here.
Keywords: laser; subrecoil laser; laser cooling; stochastic models ... See more keywords
Optimal Estimation With Missing Observations via Balanced Time-Symmetric Stochastic Models
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2017.2689685
Abstract: We consider data fusion for the purpose of smoothing and interpolation based on observation records with missing data. Stochastic processes are generated by linear stochastic models. The paper begins by drawing a connection between time… read more here.
Keywords: missing observations; time; estimation missing; observations via ... See more keywords
Large deviations for stochastic models of two-dimensional second grade fluids driven by Lévy Noise
Sign Up to like & getrecommendations! Published in 2020 at "Infinite Dimensional Analysis, Quantum Probability and Related Topics"
DOI: 10.1142/s0219025720500265
Abstract: In this paper, we establish a Freidlin–Wentzell-type large deviation principle for stochastic models of two-dimensional second grade fluids driven by Lévy noise. The weak convergence method introduced by Budhiraja, Dupuis and Maroulas plays a key… read more here.
Keywords: models two; grade fluids; two dimensional; second grade ... See more keywords
Abstract 135: Elucidating tumor evolution in pediatric cancers using stochastic models and mutation accumulation experiments
Sign Up to like & getrecommendations! Published in 2023 at "Cancer Research"
DOI: 10.1158/1538-7445.am2023-135
Abstract: Ontology-based approaches have been utilized for identifying cancer genes. However, among the thousands of mutations in pediatric cancer genes, accurate prediction of driver genes is one of the biggest challenges. A binary logistic regression model… read more here.
Keywords: cancer; stochastic models; using stochastic; accumulation experiments ... See more keywords
Linear Stochastic Models in Discrete and Continuous Time
Sign Up to like & getrecommendations! Published in 2020 at "Econometrics"
DOI: 10.3390/econometrics8030035
Abstract: The econometric data to which autoregressive moving-average models are commonly applied are liable to contain elements from a limited range of frequencies. If the data do not cover the full Nyquist frequency range of [0,π]… read more here.
Keywords: discrete continuous; continuous time; stochastic models; model ... See more keywords