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Testing against smooth stochastic trends

针对平滑随机趋势的检验

Abstract A trend estimated from an unobserved components model tends to be smoother when it is modelled as an integrated random walk rather than a random walk with drift. This article derives a test of the null hypothesis that the trend is deterministic against the alternative that it is an integrated random walk. It is assumed that the other component in the model is normally distributed white noise. Critical values are tabulated, the asymptotic distribution is derived and…

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TESTS OF COMMON STOCHASTIC TRENDS

共同随机趋势检验

This paper is concerned with tests in multivariate time series models made up of random walk (with drift) and stationary components. When the stationary component is white noise, a Lagrange multiplier test of the hypothesis that the covariance matrix of the disturbances driving the multivariate random walk is null is shown to be locally best invariant, something that does not automatically follow in the multivariate case. The asymptotic distribution of the test statistic is…

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Testing for the Constancy of Parameters over Time

检验参数是否随时间保持不变

Tests are proposed for detecting possible changes in parameters when the observations are obtained sequentially in time. While deriving the tests the alternative one has in mind specifies the parameter process as a martingale. The distribution theory of these tests relies on the large-sample results; that is, only the limiting null distributions are known (except in very special cases). The main tool in establishing these limiting distributions is weak convergence of…

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Testing for Deterministic Linear Trend in Time Series

时间序列确定性线性趋势的检验

Most powerful tests are derived for the hypothesis that deterministic linear trend occurs in time series against the alternative that trend consists of random walk subject to drift. Comparisons of these tests and of the tests suggested by LaMotte and McWhorter (1978) are made in terms of exact powers and Pitman asymptotic relative efficiencies.

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Comparisons of Tests for the Presence of Random Walk Coefficients in a Simple Linear Model

简单线性模型中随机游走系数检验的比较

The locally most powerful test is derived for the hypothesis that the regression coefficients are constant over time against the alternative that they vary according to the random walk process. When the regression equation contains the constant term only, comparisons are made with the tests suggested by LaMotte and McWhorter (1978). These are based on exact powers and on three different types of asymptotic efficiencies including the classical Pitman and Bahadur approaches…

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