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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
4.
The product partition model (PPM) is a well-established efficient statistical method for detecting multiple change points in time-evolving univariate data. In this article, we refine the PPM for the purpose of detecting multiple change points in correlated multivariate time-evolving data. Our model detects distributional changes in both the mean and covariance structures of multivariate Gaussian data by exploiting a smaller dimensional representation of correlated multiple time series. The utility of the proposed method is demonstrated through experiments on simulated and real datasets. 相似文献
5.
Alternative boundaries for CUSUM tests 总被引:1,自引:0,他引:1
Alternative boundaries for the common Recursive (or Standard) CUSUM test and the OLS-based CUSUM test for structural change
are suggested and their properties are examined by simulation of expectedp values. The poor power of the tests for early and late structural changes can be improved for the OLS-based version, whereas
this weakness of the Recursive CUSUM test cannot be overcome by the new boundaries.
Research supported by the Austrian Science Foundation (FWF) under grant SFB#010 (‘Adaptive Information Systems and Modeling
in Economics and Management Science’). 相似文献
6.
Biao Zhang 《Australian & New Zealand Journal of Statistics》2004,46(3):407-423
Demonstrated equivalence between a categorical regression model based on case‐control data and an I‐sample semiparametric selection bias model leads to a new goodness‐of‐fit test. The proposed test statistic is an extension of an existing Kolmogorov–Smirnov‐type statistic and is the weighted average of the absolute differences between two estimated distribution functions in each response category. The paper establishes an optimal property for the maximum semiparametric likelihood estimator of the parameters in the I‐sample semiparametric selection bias model. It also presents a bootstrap procedure, some simulation results and an analysis of two real datasets. 相似文献
7.
The robustness of Mauchly's sphericity test criterion when sampling from a mixture of two multivariate normal distributions is studied. The distribution of the sphericity test criterion when the sample covariance matrix has a non-central Wishart density of rank one is derived in terms of Meijer's G-functions; its distribution under the mixture model is then deduced. The robustness is studied by computing actual significance levels of the test under the mixture model using the critical values under the usual normal model. 相似文献
8.
Angelo Zanella 《Statistical Methods and Applications》1992,1(1):143-160
Summary For technological applications it can be useful to identify some simple physical mechanisms, which, on the basis of the available
knowledge of the production process, may suggest the most appropriate approach to statistical control of the random quantities
of interest. For this purpose the notion of rupture point is introduced firstly. A rupture point is characterized bym randomly arising out of control states, assumed to be mutually exclusive and stochastically independent. Shewhart's control
charts seem to represent the natural statistical tool for controlling a rupture point; however it is shown that they are fully
justified only when the hazard rates attached to the causes of failure are constant. Otherwise, typically in the presence
of time increasing hazard rates, Shewhart's control charts should be completed by a preventive intervention rule (preventive
maintenance). In the second place, the notion of dynamic instability point is introduced, which is specifically characterized
by assuming that the random quantity of interest is ruled by a stochastic differential equation with constant coefficients.
By discretization, developed according to a possibly new approach, it is shown that the former model reduces to an equation
error model, which is among the simplest used in adaptive control, and thus particularly easy to deal with in regard to parameter
estimation and the definition of the optimum control rule. 相似文献
9.
DEAN M.YOUNG PATRICK L. ODELL JOHN W. SEAMAN JR. 《Australian & New Zealand Journal of Statistics》1994,36(1):95-100
We present an explicit characterization of the joint dependency structure of an n×p matrix normal random matrix such that the p-dimensional sample mean vector is independent of all translation invariant statistics. 相似文献
10.
Xiaomo Jiang 《Journal of applied statistics》2008,35(1):49-65
Multivariate model validation is a complex decision-making problem involving comparison of multiple correlated quantities, based upon the available information and prior knowledge. This paper presents a Bayesian risk-based decision method for validation assessment of multivariate predictive models under uncertainty. A generalized likelihood ratio is derived as a quantitative validation metric based on Bayes’ theorem and Gaussian distribution assumption of errors between validation data and model prediction. The multivariate model is then assessed based on the comparison of the likelihood ratio with a Bayesian decision threshold, a function of the decision costs and prior of each hypothesis. The probability density function of the likelihood ratio is constructed using the statistics of multiple response quantities and Monte Carlo simulation. The proposed methodology is implemented in the validation of a transient heat conduction model, using a multivariate data set from experiments. The Bayesian methodology provides a quantitative approach to facilitate rational decisions in multivariate model assessment under uncertainty. 相似文献