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MOSUM tests for parameter constancy

参数恒定性的 MOSUM 检验

In this paper, tests for structural change based on moving sums (MOSUMS) of recursive and least-squares residuals are investigated. We obtain and tabulate the asymptotic critical values of the MOSUM test with recursive residuals and show that the asymptotic critical values of the MOSUM test with least-squares residuals can easily be obtained from already existing tables for the moving-estimates test. We also show that these MOSUM tests are consistent and have nontrivial…

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Additivity tests for nonlinear autoregression

非线性自回归的可加性检验

Additivity is commonly used in the statistical literature to simplify data analysis, especially in analysis of variance and in multivariate smoothing. In this paper, we propose three procedures for testing additivity in nonlinear time series analysis. The first procedure combines some smoothing techniques with analysis of variance, the second is a Lagrange multiplier test using nonparametric estimation, and the third is a permutation test which uses smoothing techniques to…

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Nonparametric tests of linearity for time series

时间序列线性的非参数检验

We introduce tests of linearity for time series based on nonparametric estimates of the conditional mean and the conditional variance. The tests are compared to a number of parametric tests and to nonparametric tests based on the bispectrum. Asymptotic expressions give bad approximations, and the null distribution under linearity is constructed using resampling of the best linear approximation. The new tests perform well on the examples tested.

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The simulation smoother for time series models

时间序列模型的模拟平滑器

Recently suggested procedures for simulating from the posterior density of states given a Gaussian state space time series are refined and extended. We introduce and study the simulation smoother, which draws from the multivariate posterior distribution of the disturbances of the model, so avoiding the degeneracies inherent in state samplers. The technique is important in Gibbs sampling with non-Gaussian time series models, and for performing Bayesian analysis of Gaussian…

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On the Behavior of a Capon-Type Spectral Density Estimator

Capon 型谱密度估计量的性质

In this paper we propose a Capon-type estimator for the spectrum of a stationary time series. This estimator may be viewed as an alternative to classical periodogram-based estimators. Its advantage is that it copes with the "leakage effect" by using implicitly automatic adaptive windowing. We show its asymptotic equivalence to a random variable which is a quadratic form in the observations, thus obtaining the asymptotic normality of the Capon estimator. We also study its…

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Asymptotic Distribution of Statistics in Time Series

时间序列统计量的渐近分布

Verifiable conditions are given for the validity of formal Edgeworth expansions for the distribution of sums $X_1 + \cdots + X_n$, where $X_i = F(Z_i, \ldots, Z_{i + p - 1})$ and $Z_1, Z_2, \ldots$ is a strict sense stationary sequence that can be written as $Z_j = g(\varepsilon_{j - k}: k \geq 0)$ with an $\operatorname{iid}$ sequence $(\varepsilon_i)$ of innovations. These models include nonlinear functions of ARMA processes $(Z_i)$ as well as certain nonlinear AR…

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Weak Convergence of the Sequential Empirical Processes of Residuals in ARMA Models

ARMA模型残差序贯经验过程的弱收敛

This paper studies the weak convergence of the sequential empirical process $\widehat{K}_n$ of the estimated residuals in ARMA$(p, q)$ models when the errors are independent and identically distributed. It is shown that, under some mild conditions, $\widehat{K}_n$ converges weakly to a Kiefer process. The weak convergence is discussed for both finite and infinite variance time series models. An application to a change-point problem is considered.

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Asymptotic Properties of Nonlinear Least Squares Estimates in Stochastic Regression Models

随机回归模型中非线性最小二乘估计的渐近性质

Stochastic regression models of the form $y_i = f_i(\theta) + \varepsilon_i$, where the random disturbances $\varepsilon_i$ form a martingale difference sequence with respect to an increasing sequence of $\sigma$-fields $\{\mathcal{G}_i\}$ and $f_i$ is a random $\mathcal{G}_{i - 1}$-measurable function of an unknown parameter $\theta$, cover a broad range of nonlinear (and linear) time series and stochastic process models. Herein strong consistency and asymptotic normality…

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Finite-Dimensional Distributions and Tail Behavior in Stationary Interval-Valued Probability Models

平稳区间值概率模型的有限维分布与尾部行为

We consider the relationship between the finite-dimensional distributions of a stationary time series model and its asymptotic behavior in the framework of interval-valued probability (IVP), a simple generalization of additive probability measures. By Caratheodory's theorem, the specification of a countably additive probability measure on the algebra of cylinders $\mathscr{C}$ uniquely defines its behavior on $\sigma(\mathscr{C})$ (containing the tail events). If the measure…

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On the Nonparametric Estimation of Covariance Functions

协方差函数的非参数估计

We describe kernel methods for estimating the covariance function of a stationary stochastic process, and show how to ensure that the estimator has the positive semidefiniteness property. From a practical viewpoint, our method is significant because it does not demand a parametric model for covariance. From a technical angle, our results exhibit a striking departure from those in more familiar cases of kernel estimation. For example, in the context of covariance estimation,…

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Large Sample Confidence Regions Based on Subsamples under Minimal Assumptions

最小假设下基于子样本的大样本置信区域

In this article, the construction of confidence regions by approximating the sampling distribution of some statistic is studied. The true sampling distribution is estimated by an appropriate normalization of the values of the statistic computed over subsamples of the data. In the i.i.d. context, the method has been studied by Wu in regular situations where the statistic is asymptotically normal. The goal of the present work is to prove the method yields asymptotically valid…

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Permutation Tests for Correlation in Regression Errors

回归误差相关性的置换检验

This article is about tests for serial, spatial, or other correlation in e, the error vector in the linear model Y = Xβ + e. The errors need not come from a particular parametric distribution such as the normal. P values are computed using permutations of the regression residuals. In the special cases that Y = e or X is a vector of Is, the tests are valid and consistent. In general, regression residuals are not exchangeable, so the tests are only approximate. It is shown,…

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Nonparametric Identification of Nonlinear Time Series: Projections

非线性时间序列的非参数模型辨识:投影方法

We study the possibility of identifying general linear and nonlinear time series models using nonparametric methods. The kernel estimators of the conditional mean and variance are used as a basis, and the properties of these quantities as model indicators are briefly discussed. Some drawbacks are pointed out, and motivated by these we introduce projections as tools of identification. The projections are especially useful for additive modeling. Expressions for the asymptotic…

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Efficient Tests of Nonstationary Hypotheses

非平稳假设的高效检验

This article proposes tests for unit root and other forms of nonstationarity that are asymptotically locally most powerful against a certain class of alternatives and have asymptotic critical values given by the chi-squared distribution. Many existing unit root tests do not share these properties. The alternatives include fractionally and seasonally fractionally differenced processes. There is considerable flexibility in our choice of null hypothesis, which can entail one or…

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Nonparametric Identification of Nonlinear Time Series: Selecting Significant Lags

非线性时间序列的非参数识别:显著滞后选择

In this article we suggest a nonparametric procedure for selecting significant lags in the model description of a general nonlinear stationary time series. The procedure can be applied to both the conditional mean and the conditional variance and is valid for heteroscedastic series. The procedure is illustrated by simulations and sunspot data, lynx data, and blowfly data are analyzed. It is indicated that projectors can be used in conjunction with the procedure for selecting…

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The Stationary Bootstrap

平稳自助法

This article introduces a resampling procedure called the stationary bootstrap as a means of calculating standard errors of estimators and constructing confidence regions for parameters based on weakly dependent stationary observations. Previously, a technique based on resampling blocks of consecutive observations was introduced to construct confidence intervals for a parameter of the m-dimensional joint distribution of m consecutive observations, where m is fixed. This…

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Stochastic Population Forecasts for the United States: Beyond High, Medium, and Low

美国人口的随机预测:超越高、中、低情景

Conventional population projections use “high,” “medium,” and “low” scenarios to indicate uncertainty, but probability interpretations are rarely given, and in any event the resulting ranges for vital rates, births, deaths, age groups sizes, age ratios, and population size cannot possibly be probabilistically consistent with one another. This article presents and implements a new method for making stochastic population forecasts that provide consistent probability intervals.…

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A Proposal for a Residual Autocorrelation Test in Linear Models

线性模型残差自相关检验的一项建议

This note proposes a test of goodness of fit for time series models based on the sum of the squared residual partial autocorrelations. The test statistic is asymptotically X2. Its small-sample performance is studied through a Monte Carlo experiment. It appears sensitive to erroneous specifications especially when the fitted model understates the order of the moving average component.

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A Laplace Approximation to the Moments of a Ratio of Quadratic Forms

二次型之比各阶矩的拉普拉斯近似

The Laplace method for approximating integrals is applied to give a general approximation for the kth moment of a ratio of quadratic forms in random variables. The technique utilises the existence of a dominating peak at the boundary point on the range of integration. As closed form and tractable formulae do not exist in general, this simple approximation, which only entails basic algebraic operations, has evident practical appeal. We exploit the approximation to provide an…

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Testing for Unit Roots in Models with Structural Change

结构变化模型中的单位根检验

This paper considers the unit root tests in models with structural change. Particular attention is given to their dependency on the limiting ratios of the subsample sizes between breaks. The dependency is analyzed in detail, and the invariant testing procedure based on a transformed model is developed. The required transformation is essentially identical to the generalized least-squares correction for heteroskedasticity. The limiting distributions of the new tests do not…

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A Note on Autoregressive Modeling

关于自回归建模的一则讨论

This paper addresses the problem of estimating vector autoregressive models. An approach to handling nonstationary (integrated) time series is briefly discussed, but the main emphasis is upon the estimation of autoregressive approximations to stationary processes. Three alternative estimators are considered–the Yule-Walker, least-squares, and Burg-type estimates–and a complete analysis of their asymptotic properties in the stationary case is given. The results obtained, when…

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Asymptotic Distributions of the Least-Squares Estimators and Test Statistics in the Near Unit Root Model with Non-Zero Initial Value and Local Drift and Trend

含非零初值、局部漂移与趋势的近单位根模型:最小二乘估计与检验的渐近分布

This paper considers the distribution of the Dickey-Fuller test in a model with non-zero initial value and drift and trend. We show how stochastic integral representations for the limiting distribution can be derived either from the local to unity approach with local drift and trend or from the continuous record asymptotic results of Sørensen [29]. We also show how the stochastic integral representations can be utilized as the basis for finding the corresponding…

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Cyclical properties of a real business cycle model

真实经济周期模型的周期特征

This paper tests the well-known real business cycle model of Kydland and Prescott (1988), using spectral methods for linear filters. Model spectra, coherencies, phase shifts, and correlations are tested against U.S. post-war data using both asymptotic and small-sample distributions. Compared with the model, the data have shorter business cycles, smaller co-movements of different macro variables, and less of a leading role for output. Copyright 1994 by John Wiley & Sons, Ltd.

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The RBC models through statistical inference: An application with french data

通过统计推断评价真实经济周期模型:法国数据应用

The aim of this paper is to evaluate the capacity of RBC models to mimic the French business cycle. We are thus led to investigate the three following assumptions on the labour market: (1) the non-time separability of leisure, (2) the indivisibility of labour and (3) the imperfect information on labour market and time-varying effort. Using the General Method of Moments, we estimate the structural parameters and we test (1) the model's hypothesis using a set of…

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