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排序方式: 共有3318条查询结果,搜索用时 15 毫秒
1.
AbstractThis paper focuses on the inference of suitable generally non linear functions in stochastic volatility models. In this context, in order to estimate the variance of the proposed estimators, a moving block bootstrap (MBB) approach is suggested and discussed. Under mild assumptions, we show that the MBB procedure is weakly consistent. Moreover, a methodology to choose the optimal length block in the MBB is proposed. Some examples and simulations on the model are also made to show the performance of the proposed procedure. 相似文献
2.
Nuttanan Wichitaksorn 《统计学通讯:理论与方法》2020,49(8):1801-1817
AbstractThis article proposes a new approach to analyze multiple vector autoregressive (VAR) models that render us a newly constructed matrix autoregressive (MtAR) model based on a matrix-variate normal distribution with two covariance matrices. The MtAR is a generalization of VAR models where the two covariance matrices allow the extension of MtAR to a structural MtAR analysis. The proposed MtAR can also incorporate different lag orders across VAR systems that provide more flexibility to the model. The estimation results from a simulation study and an empirical study on macroeconomic application show favorable performance of our proposed models and method. 相似文献
3.
Rodolphe Priam 《统计学通讯:理论与方法》2020,49(18):4468-4489
AbstractThe mean estimators with ratio depend on multiple auxiliary variables and unknown parameters in a finite population setting. We propose a new generalized approach with matrices for modeling the mutivariate mean estimators with two auxiliary variables. Our approach brings naturally a graphical analysis for comparing mean estimators. 相似文献
5.
Sets of relatively short time series arise in many situations. One aspect of their analysis may be the detection of outlying
series. We examine the performance of standard normal outlier tests applied to the means, or to simple functions of the means,
of AR(1) series, not necessarily of equal lengths. Although unequal lengths of series implies that the means have unequal
variances, that are only known approximately, it is shown that nominal significance levels hold good under most circumstances.
Thus a standard outlier test can usefully be applied, avoiding the complication of estimating the time series' parameters.
The test's power is affected by unequal lengths, being higher when the slippage occurs in one of the longer series 相似文献
6.
The problem considered is that of finding an optimum measurement schedule to estimate population parameters in a nonlinear model when the patient effects are random. The paper presents examples of the use of sensitivity functions, derived from the General Equivalence Theorem for D-optimality, in the construction of optimum population designs for such schedules. With independent observations, the theorem applies to the potential inclusion of a single observation. However, in population designs the observations are correlated and the theorem applies to the inclusion of an additional measurement schedule. In one example, three groups of patients of differing size are subject to distinct schedules. Numerical, as opposed to analytical, calculation of the sensitivity function is advocated. The required covariances of the observations are found by simulation. 相似文献
7.
On Optimality of Bayesian Wavelet Estimators 总被引:2,自引:0,他引:2
Felix Abramovich Umberto Amato Claudia Angelini 《Scandinavian Journal of Statistics》2004,31(2):217-234
Abstract. We investigate the asymptotic optimality of several Bayesian wavelet estimators, namely, posterior mean, posterior median and Bayes Factor, where the prior imposed on wavelet coefficients is a mixture of a mass function at zero and a Gaussian density. We show that in terms of the mean squared error, for the properly chosen hyperparameters of the prior, all the three resulting Bayesian wavelet estimators achieve optimal minimax rates within any prescribed Besov space for p ≥ 2. For 1 ≤ p < 2, the Bayes Factor is still optimal for (2 s +2)/(2 s +1) ≤ p < 2 and always outperforms the posterior mean and the posterior median that can achieve only the best possible rates for linear estimators in this case. 相似文献
8.
《Econometric Reviews》2007,26(1):1-24
This paper extends the current literature on the variance-causality topic providing the coefficient restrictions ensuring variance noncausality within multivariate GARCH models with in-mean effects. Furthermore, this paper presents a new multivariate model, the exponential causality GARCH. By the introduction of a multiplicative causality impact function, the variance causality effects becomes directly interpretable and can therefore be used to detect both the existence of causality and its direction; notably, the proposed model allows for increasing and decreasing variance effects. An empirical application evidences negative causality effects between returns and volume of an Italian stock market index future contract. 相似文献
9.
Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t-distribution 总被引:1,自引:0,他引:1
Adelchi Azzalini Antonella Capitanio 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2003,65(2):367-389
Summary . A fairly general procedure is studied to perturb a multivariate density satisfying a weak form of multivariate symmetry, and to generate a whole set of non-symmetric densities. The approach is sufficiently general to encompass some recent proposals in the literature, variously related to the skew normal distribution. The special case of skew elliptical densities is examined in detail, establishing connections with existing similar work. The final part of the paper specializes further to a form of multivariate skew t -density. Likelihood inference for this distribution is examined, and it is illustrated with numerical examples. 相似文献
10.
Cédric Béguin Beat Hulliger 《Journal of the Royal Statistical Society. Series A, (Statistics in Society)》2004,167(2):275-294
Summary. As a part of the EUREDIT project new methods to detect multivariate outliers in incomplete survey data have been developed. These methods are the first to work with sampling weights and to be able to cope with missing values. Two of these methods are presented here. The epidemic algorithm simulates the propagation of a disease through a population and uses extreme infection times to find outlying observations. Transformed rank correlations are robust estimates of the centre and the scatter of the data. They use a geometric transformation that is based on the rank correlation matrix. The estimates are used to define a Mahalanobis distance that reveals outliers. The two methods are applied to a small data set and to one of the evaluation data sets of the EUREDIT project. 相似文献