probability model
81Markov model — In probability theory, a Markov model is a stochastic model that assumes the Markov property. Generally, this assumption enables reasoning and computation with the model that would otherwise be intractable. Contents 1 Introduction 2 Markov chain… …
82Quasispecies model — The quasispecies model is a description of the process of the Darwinian evolution of certain self replicating entities within the framework of physical chemistry. Put simply, a quasispecies is a large group or cloud of related genotypes that… …
83Parametric model — A parametric model is a set of related mathematical equations in which alternative scenarios are defined by changing the assumed values of a set of fixed coefficients (parameters). In statistics, a parametric model is a parametrized family of… …
84Neglect of probability — The neglect of probability bias, a type of cognitive bias, is the tendency to completely disregard probability when making a decision under uncertainty and is one simple way in which people regularly violate the normative rules for decision… …
85Bag of words model — The bag of words model is a simplifying assumption used in natural language processing and information retrieval. In this model, a text (such as a sentence or a document) is represented as an unordered collection of words, disregarding grammar… …
86Time-Inhomogeneous Hidden Bernoulli Model — (TI HBM) is an alternative to Hidden Markov Model (HMM) for Automatic Speech Recognition. Contrary to HMM, the state transition process in TI HBM is not a Markov dependent process, rather it is a generalized Bernoulli (an independent) process.… …
87Dependability state model — A dependability state diagram is a method for modelling a system as a Markov chain. It is used in reliability engineering for availability and reliability analysis.[1]. A simple state model with two states It consists of creating a finite state… …
88List of probability distributions — Many probability distributions are so important in theory or applications that they have been given specific names.Discrete distributionsWith finite support* The Bernoulli distribution, which takes value 1 with probability p and value 0 with… …
89Maximum entropy probability distribution — In statistics and information theory, a maximum entropy probability distribution is a probability distribution whose entropy is at least as great as that of all other members of a specified class of distributions. According to the principle of… …
90Shannon–Weaver model — The Shannon–Weaver model of communication has been called the mother of all models. [cite book | title = Joint Cognitive Systems: Foundations of Cognitive Systems Engineering | author = David D. Woods and Erik Hollnagel | pusblisher = CRC Press | …
