Dynamic Linear Models with R

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动力线性模型和动力非线性模型相对应

State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms.

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https://bbs.pinggu.org/forum.php?mod=viewthread&tid=490218&page=1#pid2946000
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