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无限方差过程的稳健因果性检验AI 解读

This paper develops a robust causality test for time series with infinite variance innovation processes. First, we introduce a measure of dependence for vector nonparametric linear processes, and derive the asymptotic distribution of the test statistic by Taniguchi et al. (1996) in the infinite variance case. Second, we construct a weighted version of the generalized empirical likelihood (GEL) test statistic, called the self-weighted GEL statistic in the time domain. The…

标量参数的方差稳定化AI 解读

Summary We present a variance stabilizing transformation for inference about a scalar parameter that is estimated by a function of a multivariate M-estimator. The transformation proposed is automatic, computationally simple and can be applied quite generally. Though it is based on an intuitive notion and entirely empirical, the transformation is shown to have an appropriate justification in providing variance stabilization when viewed from both parametric and nonparametric…

偏斜指数幂分布的统计推断AI 解读

When the analysis of real data indicates that normality assumptions are untenable, more flexible models that cope with the most prevalent deviations from normality can be adopted. In this context, the skew exponential power (SEP) distribution warrants special attention, because it encompasses distributions having both heavy tails and skewness, it allows likelihood inference, and it includes the normal model as a special case. This article concerns likelihood inference about…

线性模型残差自相关检验的一项建议AI 解读

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.

线性模型残差自相关检验的一种方案AI 解读

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.

多元 M 估计中经验似然与经验鞍点近似的关系AI 解读

By comparing the expansions of the empirical log-likelihood ratio and the empirical cumulant generating function calculated at the saddlepoint, we investigate the relationship between empirical likelihood and empirical saddlepoint approximations. This leads to a nonparametric approximation of the density of a multivariate M-estimator based on the empirical likelihood and, on the other hand, it provides nonparametric confidence regions based on the empirical cumulant…

多元 M 估计中经验似然与经验鞍点近似的关系AI 解读

By comparing the expansions of the empirical log-likelihood ratio and the empirical cumulant generating function calculated at the saddlepoint, we investigate the relationship between empirical likelihood and empirical saddlepoint approximations. This leads to a nonparametric approximation of the density of a multivariate M-estimator based on the empirical likelihood and, on the other hand, it provides nonparametric confidence regions based on the empirical cumulant…