The main purpose of this work is to contribute the study set-valued random variables by providing a kind Wold decomposition theorem for interval-valued processes. As set not vector space, as established in 1938 Herman applicable them. So, notion pseudovector space introduced and used establish generalization that works covariance stationary time series Before this, autoregressive moving-average...

Related DatabasesWeb of Science You must be logged in with an active subscription to view this.Article DataHistorySubmitted: 30 September 2020Accepted: 22 June 2021Published online: 26 October 2021Keywordscontinuous-time ARMA processes, transition density, pricing derivativesAMS Subject Headings60G99, 91G60, 91G80Publication DataISSN (online): 1945-497XPublisher: Society for Industrial and Appl...

We show that the covariance function of a second-order stationary vector Markov regime switching time series has a vector ARMA(p; q) representation, where upper bounds for p and q are elementary functions of the number of regimes. These bounds apply to vector Markov regime switching processes with both mean-variance and autoregressive switching. This result yields an easily computed method for ...

In this paper, the short-term load forecast by use of autoregressive moving average (ARMA) model including non-Gaussian process considerations is proposed. In the proposed method, the concept of cumulant and bispectrum are embedded into the ARMA model in order to facilitate Gaussian and non-Gaussian process. With embodiment of a Gaussianity verification procedure, the forecasted model is identi...

The objective of this study was to investigate the genetic basis of high level aminoglycoside resistance in Acinetobacter baumannii clinical isolates from Beijing, China. 173 A. baumannii clinical isolates from hospitals in Beijing from 2006 to 2009 were first subjected to high level aminoglycoside resistance (HLAR, MIC to gentamicin and amikacin>512 µg/mL) phenotype selection by broth microdil...

An approach to handling colored observation noise in large least-squares (LS) problems is presented. The handling of colored noise is reduced to the problem of solving a Toeplitz system of linear equations. The colored noise is represented as an auto regressive moving-average (ARMA) process. Stability and invertability of the ARMA model allows the solution of the Toeplitz system to be reduced t...

As we have remarked, dependence is very common in time series observations. To model this time series dependence, we start with univariate ARMA models. To motivate the model, basically we can track two lines of thinking. First, for a series xt, we can model that the level of its current observations depends on the level of its lagged observations. For example, if we observe a high GDP realizati...

In this paper we analyze the asymptotic properties of the popular distribution tail index estimator by Hill (1975) for dependent, heterogeneous processes. We develop new extremal dependence measures that characterize a massive array of linear, nonlinear, and conditional volatility processes with long or short memory. We prove that the Hill estimator is weakly and uniformly weakly consistent for...