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This article establishes the functional coefficient moving average mod-el (FMA), which allows the coefficient of the classical moving average model to adapt with a covariate. The functional coefficien...
In practice, several time series exhibit long-range dependence or per-sistence in their observations, leading to the development of a number of estimation and prediction methodologies to account for t...
In this paper, we introduce a modified test statistic, by applying moving average method and present a new cdf estimator to estimate the joint entropy of the type-II censored data. We also establish a...
Vocal tract resonance characteristics in acoustic speech signals are classically tracked using frame-by-frame point estimates of formant frequencies followed by candidate selection and smoothing using...
Consider error terms i of a moving average process MA(q), where i = Pq j=0 "i−j and "i - independent identically distributed (i.i.d.) random variables. We recognize a term i as a local max...
We obtain the rate of growth of long strange segments and the rate of decay of infinite horizon ruin probabilities for a class of infinite moving average processes with exponentially light tails. Th...
The paper is devoted to a study of the extremal rearrangement property of statistical solutions of Burgers' equation with initial input generated by the Brownian motion or by a Poisson process.
A convolution semigroup of probability generating functions and its related operator ⊙F are used to construct a class of stationary Z+-valued autoregressive moving average (ARMA) processes. Several ...
In this paper, we consider a continuous-time autoregressive fractionally integrated moving average(CARFIMA) model, which is defined as the stationary solution of a stochastic differential equation dr...
The first-order moving average model or MA(1) is given by Xt = Zt − 0Zt−1, with independent and identically distributed {Zt}. This is arguably the simplest time series model that one ca...

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