Supereecient Estimation of Multivariate Trend

Superefficient Estimation of Multivariate Trend

The question of recovering a multiband signal from noisy observations motivates a model in which the multivariate data points consist of an unknown deterministic trend Ξ observed with multivariate Gaussian errors. A cognate random trend model suggests affine shrinkage estimators Ξ̂A and Ξ̂B for Ξ, which are related to an extended Efron-Morris estimator. When represented canonically, Ξ̂A performs c...

TREND-CYCLE ESTIMATION USING FUZZY TRANSFORM OF HIGHER DEGREE

In this paper, we provide theoretical justification for the application of higher degree fuzzy transform in time series analysis. Under the assumption that a time series can be additively decomposed into a trend-cycle, a seasonal component and a random noise, we demonstrate that the higher degree fuzzy transform technique can be used for the estimation of the trend-cycle, which is one of the ba...

Estimation of the Multivariate Normal Mean under the Extended Reflected Normal Loss Function

A Nonparametric Regression Spectrum : Estimation, Asymptotic Properties and Data Analysis

Classical spectral analysis in statistics considers decomposition of stationary time series into sinusoidal components. The autocovariance and the spectrum are fundamental elements for analyzing a given time series both in time and frequency domain. However, in practice one frequently observes nonstationary time series. In order to apply spectral analysis to these processes, an extension of the...

Step change point estimation in the multivariate-attribute process variability using artificial neural networks and maximum likelihood estimation

In some statistical process control applications, the combination of both variable and attribute quality characteristics which are correlated represents the quality of the product or the process. In such processes, identification the time of manifesting the out-of-control states can help the quality engineers to eliminate the assignable causes through proper corrective actions. In this paper, f...