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季节性时间序列建模与预测的另一种方法AI 解读

This article proposes an alternative methodology for modeling and forecasting seasonal series. The approach is in the Bayesian autoregression tradition pioneered by Doan, Litterman, and Sims and builds seasonality directly into the prior of the coefficients of the model by means of a set of uncertain linear restrictions. As an illustration, the method is applied to 10 U.S. quarterly macroeconomic series. For each series, the author compares the forecasting performance of a…

基于累积卡方统计量最大分量的多重比较程序AI 解读

Multiple comparison procedures based on the maximal component of the cumulative chi-squared statistic are discussed. The Markov properties for the successive components of the cumulative chi-squared statistic are proved and applied for obtaining the p- value of the maximal component in each of the one-way and the two-way analysis of variance models and the two-way contingency table. The power of the multiple comparison procedure is compared with those for some well-known…

存在混杂因素时的时变加速失效时间模型估计AI 解读

Cox & Oakes (1984, p. 66) introduced the ‘strong version’ of the accelerated failure time model with time-dependent exposures. We provide conditions under which this model could be used to estimate, from observational data, the causal effect of a time-varying exposure or treatment on time to an event of interest in the presence of time-dependent confounding variables. We propose a class of semiparametric tests and estimators for the model parameters. This class contains an…

非线性时间序列建模中残差自相关的渐近标准误AI 解读

The asymptotic distribution of residual autocorrelations for some very general nonlinear time series models is derived. This includes the important class of threshold models. Consequently more accurate standard errors for residual autocorrelations can be obtained facilitating model diagnostic checkings in many situations. A small simulation result applying the methodology to threshold models is reported.

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若干非参数变点估计量的渐近行为AI 解读

Consider a sequence $X_1, X_2,\ldots, X_n$ of independent random variables, where $X_1, X_2,\ldots, X_{n\theta}$ have distribution $P,$ and $X_{n\theta + 1}, X_{n\theta + 2},\ldots, X_n$ have distribution $Q$. The change-point $\theta \in (0,1)$ is an unknown parameter to be estimated, and $P$ and $Q$ are two unknown probability distributions. The nonparametric estimators of Darkhovskh and Carlstein are imbedded in a more general framework, where random seminorms are applied…

带切换的动态线性模型AI 解读

The problem of modeling change in a vector time series is studied using a dynamic linear model with measurement matrices that switch according to a time-varying independent random process. We derive filtered estimators for the usual state vectors and also for the state occupancy probabilities of the underlying nonstationary measurement process. A maximum likelihood estimation procedure is given that uses a pseudo-expectation-maximization algorithm in the initial stages and…

带切换机制的动态线性模型AI 解读

The problem of modeling change in a vector time series is studied using a dynamic linear model with measurement matrices that switch according to a time-varying independent random process. We derive filtered estimators for the usual state vectors and also for the state occupancy probabilities of the underlying nonstationary measurement process. A maximum likelihood estimation procedure is given that uses a pseudo-expectation-maximization algorithm in the initial stages and…

回归参数稳定性的贝叶斯显著性检验AI 解读

This paper presents a Bayesian significance test for stationarity of a regression equation using the highest posterior density credible set. In addition, a solution to the Behrens-Fisher problem is provided. From a Monte Carlo simulation study, it has been shown that the Bayesian significance test has stronger power than the Cusum and the Cusum of squares tests. The Bayesian significance test may be useful in detecting individual parameter nonstationarity.

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初始均值未知时正态均值变化的序贯检测AI 解读

Three stopping rules are proposed to detect a change in a normal mean, when the initial value of the mean is unknown but an estimate obtained from a training sample is available. Asymptotic approximations are given for the average run length when there is no change. Under certain hypotheses about the length of time before the change occurs and the magnitude of the change, we obtain asymptotic approximations for the expected delay in detection in terms of the corresponding…

含内生解释变量的面板数据模型识别AI 解读

This paper provides sufficient conditions for the identification of both static and dynamic models containing endogenous regressors from panel data by utilizing the restrictions across time periods on the parameters. It is shown that identification is achieved under quite weak conditions even in the presence of a general pattern of correlation between the errors and the time-varying variables. Efficient estimation procedures for the models considered and some specification…

风险率变点的统计推断AI 解读

We discuss inference based on the likelihood ratio process for a hazard rate change point. A random change of time scale transforms the empirical process into a Poisson process which enables us to derive large deviation approximations to the significance level of the likelihood ratio test. We derive approximate confidence regions for the change point and joint confidence regions for the change point and size of change. The effect of censorship is also discussed. The methods…

回归参数稳定性的贝叶斯显著性检验AI 解读

This paper presents a Bayesian significance test for stationarity of a regression equation using the highest posterior density credible set. In addition, a solution to the Behrens-Fisher problem is provided. From a Monte Carlo simulation study, it has been shown that the Bayesian significance test has stronger power than the Cusum and the Cusum of squares tests. The Bayesian significance test may be useful in detecting individual parameter nonstationarity.

未知分布下变点的渐近有效估计AI 解读

Suppose $X_1,\cdots, X_n$ are distributed according to a probability measure under which $X_1,\cdots, X_n$ are independent, $X_1 \sim F_0$, for $i = 1,\cdots, \lbrack\theta_n n\rbrack$ and $X_i \sim F^{(n)}$ for $i = \lbrack\theta_nn\rbrack + 1, \cdots, n$ where $\lbrack x\rbrack$ denotes the integer part of $x$. In this paper we consider the asymptotic efficient estimation of $\theta_n$ when the distributions are not known. Our estimator is efficient in the sense that if $F^{(n)} = F_{\eta_n}, \eta_n \rightarrow 0$…

危险率变点模型中似然比检验的一个问题AI 解读

A likelihood ratio test for constant hazard against a step change alternative has received considerable attention in recent years. Additional information in the maximum likelihood estimate of the change-point can seriously affect interpretation of test results. Some simple modifications are considered for which exact percentage points can be derived. Monte Carlo power and mean squared error comparisons are encouraging.

工资收入与生育时点及间隔：瑞典纵向数据证据AI 解读

This paper considers the formulation, estimation, and evaluation of semiparametric multistates duration models with time-varying regressors and unobservables correlated over spells. The authors' models are applied to test a dynamic version of the neoclassical theory of fertility. Using Swedish data, they find that rising female wages over the lifecycle delay times to all conceptions, but barely affect childlessness. The authors estimate a model that predicts fertility…

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CUSUM 程序的决策论最优性AI 解读

Suppose $X_1, X_2, \ldots$ are independent random variables such that for some unknown $\nu$, each of $X_1, \ldots, X_{\nu - 1}$ is distributed according to $F_0$, while $X_\nu, X_{\nu + 1}, \ldots$ are all distributed according to $F_1$. We prove a result of Moustakides that claims that the CUSUM procedures are optimal in the sense of Lorden. We do that by proving that the procedures are Bayes for some stochastic mechanism of generating $\nu$.

多个变化点的最大似然估计AI 解读

Maximum likelihood estimation of the locations of changes in sequences of independent categorical random variables when there are known lower bounds on the lengths of the sub-sequences between the change points is discussed. A method is developed which finds one of the maximum likelihood solutions. The problem of estimating the number of changed segments is discussed and some numerical results about the precision of the estimates of the locations of changes are presented.…

股票收益中的异方差AI 解读

ABSTRACT We use predictions of aggregate stock return variances from daily data to estimate time‐varying monthly variances for size‐ranked portfolios. We propose and estimate a single factor model of heteroskedasticity for portfolio returns. This model implies time‐varying betas. Implications of heteroskedasticity and time‐varying betas for tests of the capital asset pricing model (CAPM) are then documented. Accounting for heteroskedasticity increases the evidence that…

CUSUM 与平方 CUSUM 检验的局部功效AI 解读

We consider the local power of the cusum and cusum of squares tests for structural change in the linear regression model. We show that the local power of the cusum of squares test equals its size for a wide class of structural changes, as compared to a nontrivial local power for the cusum test. The conventional ranking of these procedures is thus reversed.

生物医学时间序列的建模与监测AI 解读

A framework for modeling and monitoring medical time series is developed, based on extensions to the linear dynamic model. The approach is designed to provide for on-line, recursive updating and inference for time series that are subject to several forms of potential discontinuous change, and that may have missing values. The models and methods introduced are illustrated with three biomedical series.

均值变化最大似然检验的渐近分布AI 解读

For the maximum likelihood tests for a change in the mean of independent random variables, it is proved that the limit distribution is a double exponential, i.e. Gumbel, distribution. Our results also explain why the maximum likelihood methods are very powerful on the tails.