CHASE 发表于 2025-3-23 11:24:22
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过份艳丽 发表于 2025-3-23 17:17:17
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 sequgregarious 发表于 2025-3-23 18:08:07
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Statistical Inference for Discrete Time Stochastic Processes978-81-322-0763-4Series ISSN 2191-544X Series E-ISSN 2191-5458Haphazard 发表于 2025-3-24 08:33:34
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SpringerBriefs in Statisticshttp://image.papertrans.cn/s/image/876438.jpg先兆 发表于 2025-3-24 15:57:36
https://doi.org/10.1007/978-81-322-0763-4Bootstrap; Estimating Functions; Non-Gaussian Sequences; Stationary Random Sequences; Statistical Infere用手捏 发表于 2025-3-24 19:42:14
http://reply.papertrans.cn/88/8765/876438/876438_19.png运气 发表于 2025-3-25 02:46:47
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