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部分观测时间序列的非线性检验AI 解读

We have implemented a Lagrange multiplier test specifically for the alternative of a nonlinear continuous-time autoregressive model with the instantaneous mean having one degree of nonlinearity. The test is then extended to testing for the alternative of general nonlinear continuous-time autoregressive models with multiple degrees of nonlinearity. The performance of the test in the finite-sample case is compared with several existing tests for nonlinearity including Keenan's…

多窗多变量谱估计的统一视角AI 解读

The orthogonal multitaper framework for cross‐spectral estimators provides a simple unifying structure for determining the corresponding statistical properties. Here cross‐spectral estimators are represented by a weighted average of orthogonally‐tapered cross‐periodograms, with the weights corresponding to a set of rescaled eigenvalues. Such a structure not only encompasses the Thomson estimators, using Slepian and sine tapers, but also Welch's weighted overlapped segment…

成组失效时间数据的半参数回归分析AI 解读

Inference procedures based on the partial likelihood function for the Cox proportional hazards model have been generalised to the case in which the data consist of a large number of independent small groups of correlated failure time observations (Lee, Wei [amp ] Amato, 1992; Liang, Self [amp ] Chang, 1993; Cai [amp ] Prentice, 1997). However, the Cox model may not fit the data well. A class of linear transformation models, which includes the proportional hazards and odds…

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局部平稳过程的似然近似AI 解读

A new approximation to the Gaussian likelihood of a multivariate locally stationary process is introduced. It is based on an approximation of the inverse of the covariance matrix of such processes. The new quasi likelihood is a generalization of the classical Whittle likelihood for stationary processes. Several approximation results are proved for the likelihood function. For parametric models, asymptotic normality and efficiency of the resulting estimator are derived for…

Motivated by an application in computerized adaptive tests, we consider the following sequential design problem.There are $J$ jobs to be processed according to a predetermined order. A single machine is available to process these $J$ jobs. Each job under processing evolves stochastically as a Markov chain and earns rewards as it is processed, not otherwise. The Markov chain has transition probabilities parameterized by an unknown parameter $\theta$. The objective is to…

指数族中序贯检验与固定样本量检验错误概率的渐近近似AI 解读

Asymptotic approximations for the error probabilities of sequential tests of composite hypotheses in multiparameter exponential families are developed herein for a general class of test statistics, including generalized likelihood ratio statistics and other functions of the sufficient statistics. These results not only generalize previous approximations for Type I error probabilities of sequential generalized likelihood ratio tests, but also pro- vide a unified treatment of…

回归模型选择的渐近极小极大遗憾规则与维数惩罚AI 解读

This paper addresses the topic of model selection in regression.We emphasize the case of two models, testing which model provides a better prediction based on $n$ observations. Within a family of selection rules, based on maximizing a penalized log-likelihood under a normal model, we search for asymptotically minimax rules over a class $\mathscr{G}$ of possible joint distributions of the explanatory and response variables. For the class $\mathscr{G}$ of multivariate normal…

大规模伯努利数据的平滑样条 ANOVA 模型与随机化 GACVAI 解读

We propose the randomized Generalized Approximate Cross Validation (ranGACV) method for choosing multiple smoothing parameters in penalized likelihood estimates for Bernoulli data. The method is intended for application with penalized likelihood smoothing spline ANOVA models. In addition we propose a class of approximate numerical methods for solving the penalized likelihood variational problem which, in conjunction with the ranGACV method allows the application of smoothing…

乘法级联的统计估计AI 解读

The probability distribution of the cascade generators in a random multiplicative cascade represents a hidden parameter which is reflected in the fine scale limiting behavior of the scaling exponents (sample moments) of a single sample cascade realization as a.s.constants.We identify a large class of cascade generators uniquely determined by these scaling exponents. For this class we provide both asymptotic consistency and confidence intervals for two different estimators of…

In this paper we propose a sequential testing procedure to determine the order of differencing in seasonally observed time series processes, which builds upon existing approaches developed for nonseasonal series. We allow for the possible presence of multiple unit roots at both the zero and seasonal frequencies of the data. Multiple seasonal unit roots can be useful in circumstances where one does not wish to take logarithms of the data‐set at hand. Multiple unit roots at…

This paper proposes a residual-based Lagrange multiplier (LM) test for a null that the individual observed series are stationary around a deterministic level or around a deterministic trend against the alternative of a unit root in panel data. The tests which are asymptotically similar under the null, belong to the locally best invariant (LBI) test statistics. The asymptotic distributions of the statistics are derived under the null and are shown to be normally distributed.…

异方差下线性自回归动态的检验AI 解读

A puzzling characteristic of asset returns for various frequencies is the often observed positive autocorrelation at lag one. To some extent this can be explained by standard asset pricing models when assuming time-varying risk premia. However, one often finds better results when directly fitting an autoregressive model, for which there is little economic foundation. One may ask whether the underlying process does in fact contain an autoregressive component. It is therefore…

A generalization of martingale estimating functions is presented which is useful when there are no natural or easily calculated martingales that can be used to construct a class of martingale estimating functions. An estimating function of the new type, which is based on linear predictors, is called a prediction‐based estimating functions. Special attention is given to classes of prediction‐based estimating functions given by a finite‐dimensional space of predictors. It is…

马尔可夫过程、双向自回归与平稳及非平稳自回归的有限样本推断AI 解读

In this paper, we develop finite-sample inference procedures for stationary and nonstationary autoregressive (AR) models. The method is based on special properties of Markov processes and a split-sample technique. The results on Markovian processes (intercalary independence and truncation) only require the existence of conditional densities. They are proved for possibly nonstationary and/or non-Gaussian multivariate Markov processes. In the context of a linear regression…

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条件异方差下鞅假设的谱检验AI 解读

We study the asymptotic distribution of the sample standardized spectral distribution function when the observed series is a conditionally heteroscedastic martingale difference. We show that the asymptotic distribution is no longer a Brownian bridge but another Gaussian process. Furthermore, this limiting process depends on the covariance structure of the second moments of the series. We show that this causes test statistics based on the sample spectral distribution, such as…

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更简便的仿射不变多元分布无关符号检验AI 解读

A simpler multivariate sign test is proposed that uses the transformation-retransformation approach of Chakraborty, Chaudhuri, and Oja together with a directional transformation due to Tyler. This produces a multivariate sign test that is practical to apply to data of any dimension, makes minimal assumptions about the underlying distribution, and has a small-sample distribution-free property over a broad class of population models. It is shown to perform very well in…