Titlebook: Statistical Inference for Discrete Time Stochastic Processes; M. B. Rajarshi Book 2013 The Author(s) 2013 Bootstrap.Estimating Functions.N

CHASE

Non-Gaussian ARMA Models,ch as exponential, Weibull, gamma, inverse Gaussian, and Cauchy. In some cases, maximum likelihood estimation is tractable. In other cases, regularity conditions are not met. Estimation is then carried out based on properties of the marginal distribution of the process and mixing properties such as

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Book 2013hastic models. Construction of confidence intervals based on estimating functions is discussed in some detail. Kernel based estimation of joint density and conditional expectation are also discussed. Bootstrap and other resampling procedures for dependent sequences such as Markov chains, Markov sequ

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創(chuàng)新

Statistical Inference for Discrete Time Stochastic Processes978-81-322-0763-4Series ISSN 2191-544X Series E-ISSN 2191-5458

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Emmenagogue

SpringerBriefs in Statisticshttp://image.papertrans.cn/s/image/876438.jpg

先兆

https://doi.org/10.1007/978-81-322-0763-4Bootstrap; Estimating Functions; Non-Gaussian Sequences; Stationary Random Sequences; Statistical Infere

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