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- W174452842 abstract "While modelling physiological systems, randomness exists at several intertwined levels ranging from errors in measurement to intrinsically stochastic (random) processes, such as diffusion and Poisson processes. In this chapter, we walk the reader through several stages of quantifying probability, beginning with a heuristic description of the concept of chance, random variables, statistical observation, basic probability distributions, limit theorems, and the basics of random processes. Further, we proceed with identification and estimation of stochastic models and present standard techniques including correlation and regression, statistical comparisons, classification, clustering, discriminant analysis, and principal components. We then continue with advanced methods embracing the framework of Markov chains (e.g., Chapman–Kolmogorov equation) and Markov processes (e.g., stochastic differential equations and Kalman filtering). Throughout the chapter, we present examples relating the discussed methods to problems encountered in physiology. We conclude that stochastic methods and probability are inherent in many physiological models and are essential for their characterization." @default.
- W174452842 created "2016-06-24" @default.
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- W174452842 date "2014-01-01" @default.
- W174452842 modified "2023-09-25" @default.
- W174452842 title "Stochastic Models of Physiology" @default.
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- W174452842 doi "https://doi.org/10.1016/b978-0-12-411557-6.00011-2" @default.
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