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Titlebook: Random Coefficient Autoregressive Models: An Introduction; An Introduction Des F. Nicholls,Barry G. Quinn Book 1982 Springer-Verlag New Yor

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31#
發(fā)表于 2025-3-27 00:41:34 | 只看該作者
Des F. Nicholls,Barry G. Quinnides comprehensive coverage of the entire breadth of the field, gives readers access to all major sub-fields and illustrates their interconnectedness with other disciplines. The nearly 1,100 entries delve deep into key areas of gerontology and population aging—such as successful aging, disablement,
32#
發(fā)表于 2025-3-27 04:56:30 | 只看該作者
33#
發(fā)表于 2025-3-27 05:31:43 | 只看該作者
0930-0325 e non-linear models so far considered in the statistical literature, in that their analysis is quite tractable. It has been possible to find conditions for stationarity and stability, to derive estimates of the unknown parameters, to establish asymptotic properties of these estimates and to obtain t
34#
發(fā)表于 2025-3-27 12:35:38 | 只看該作者
35#
發(fā)表于 2025-3-27 14:15:33 | 只看該作者
Testing the Randomness of the Coefficients,se of the theory derived in chapter 4 to test what is perhaps the most relevant hypothesis, namely that Σ = 0, that is, that the data come from a fixed coefficient autoregression. This chapter examines the testing of hypotheses in general, and in particular, two tests for the hypothesis that Σ = 0.
36#
發(fā)表于 2025-3-27 19:24:06 | 只看該作者
An Application,en applied. An extensive account of the statistical and historical aspects of the modelling of the lynx data is contained in Campbell and Walker (1977) (where the data are reproduced since the original sources are relatively inaccessible) and the discussion which follows.
37#
發(fā)表于 2025-3-28 00:22:32 | 只看該作者
38#
發(fā)表于 2025-3-28 02:24:25 | 只看該作者
Introduction, models to be the “best” class of model to fit to a set of real data, although one tacitly makes the assumption that the linear model under consideration is a close approximation to physical reality. A number of factors have resulted in a consideration of different classes of non-linear models, not
39#
發(fā)表于 2025-3-28 10:20:41 | 只看該作者
40#
發(fā)表于 2025-3-28 13:04:01 | 只看該作者
Least Squares Estimation of Scalar Models,tionary time series {X(t)} satisfies such an equation, it is necessary to estimate the unknown parameters in order to provide predictors of X(t) given past values of the process. Estimation procedures for fixed coefficient autoregressions are well established, and the asymptotic properties of these
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