Titlebook: Applied Probability; From Random Sequence Valérie Girardin,Nikolaos Limnios Textbook 2018 Springer Nature Switzerland AG 2018 Probability.R

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書目名稱Applied Probability影響因子(影響力)




書目名稱Applied Probability影響因子(影響力)學科排名




書目名稱Applied Probability網絡公開度




書目名稱Applied Probability網絡公開度學科排名




書目名稱Applied Probability被引頻次




書目名稱Applied Probability被引頻次學科排名




書目名稱Applied Probability年度引用




書目名稱Applied Probability年度引用學科排名




書目名稱Applied Probability讀者反饋




書目名稱Applied Probability讀者反饋學科排名

炸壞

Conditioning and Martingales,st supposed to exist, which is true for all random variables taking values in .. Still, conditional expectation is defined in the most general case. A section is dedicated to determining practically conditional distributions and expectations, and another to the linear model in which a random phenome

繼而發(fā)生

Markov Chains,chains generalize sequences of independent random variables to variables linked by a simple dependence relation. They model for example, phase transitions of substances between solid, liquid and gaseous states, passages of systems between up and down states, etc. A random sequence . is a Markov chai

壁畫

Markov and Semi-Markov Processes,uously counted over the positive real line. Markov processes are continuous-time processes that share the Markov property with the discrete-time Markov chains. Their future evolution conditional to the past depends only on the last occupied state. Their extension to the so-called semi-Markov process

Ordeal

溝通

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Continuous Time Stochastic Processes,A stochastic process represents a system, usually evolving along time, which incorporates an element of randomness, as opposed to a deterministic process.

寬度

nocturnal

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EXALT

https://doi.org/10.1007/978-3-319-97412-5Probability; Random sequences; Random processes; Markov chains; Semi-Markov processes; Martingales; Stocha