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TESTS FOR TAR MODELS VS. STAR MODELS-A SEPARATE FAMILY OF HYPOTHESES APPROACH

机译:TAR模型的测试与 星模型 - 单独的假设家庭方法

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The threshold autoregressive (TAR) model and the smooth threshold autoregressive (STAR) model have been popular parametric nonlinear time series models for the past three decades or so. As yet there is no formal statistical test in the literature for one against the other. The two models are fundamentally different in their autoregressive functions, the TAR model being generally discontinuous while the STAR model is smooth (except in the limit of infinitely fast switching for some cases). Following the approach initiated by Cox (1961, 1962), we treat the test problem as one of separate families of hypotheses. The test statistic under a STAR model is shown to follow asymptotically a chi-squared distribution, and the one under a TAR model can be expressed as a functional of a chi-squared process. We present numerical results with both simulated and real data to assess the performance of our procedure.
机译:阈值自回归(焦油)模型和平滑的阈值自回归(星级)模型是过去三十年左右的流行参数非线性时间序列模型。 尚未在文献中没有正式统计测试,以适用于另一个。 这两种型号在其自回归功能中基本不同,Tar模型通常是不连续的,而星形模型是平滑的(除了在某些情况下无限快速切换的限制除外)。 遵循Cox(1961,1962)发起的方法,我们将测试问题视为单独的假设系列之一。 明星模型下的测试统计显示在渐近的渐近分布下,并且焦油模型下的一个可以表示为Chi方向的功能。 我们使用模拟和实际数据呈现数值结果,以评估我们程序的性能。

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