On Sequential Comparisons of Means of First-Order Autoregressive Models.
On stationarity of a multiple doubly stochastic model
On the autocorrelation function of a trended series.
Equations are derived for the autocorrelation function of a trended series. The special case of a linear trend is analysed in detail. It is shown that the zero of the autocorrelation function of a trended series is, in general, only dependent on the length of the series. This result is valid for stochastic and deterministic trends.
On the Bayes approach in general multiple autoregressive series
On the computation of the exact distribution of power divergence test statistics
In this paper we introduce several algorithms to generate all the vectors in the support of a multinomial distribution. Computational studies are carried out to analyze their efficiency with respect to the CPU time and to calculate their efficiency frontiers. The proposed algorithm is used to calculate exact distributions of power divergence test statistics under the hypothesis of uniformity. Finally, several exact power comparisons are done for different divergence statistics and families of alternatives...
On the efficiency of procedures for estimation of parameters in ARIMA models.
The paper discusses the implementation of the Newton-Raphson iterative method of estimation of parameters in the autoregressive integrated moving average (ARIMA) models. The efficiency of this method has been compared with other well known methods of estimation.
On the estimation of the autocorrelation function
The autocorrelation function has a very important role in several application areas involving stochastic processes. In fact, it assumes the theoretical base for Spectral analysis, ARMA (and generalizations) modeling, detection, etc. However and as it is well known, the results obtained with the more current estimates of the autocorrelation function (biased or not) are frequently bad, even when we have access to a large number of points. On the other hand, in some applications, we need to perform...
On the extremal behavior of a Pareto process: an alternative for ARMAX modeling
In what concerns extreme values modeling, heavy tailed autoregressive processes defined with the minimum or maximum operator have proved to be good alternatives to classical linear ARMA with heavy tailed marginals (Davis and Resnick [8], Ferreira and Canto e Castro [13]). In this paper we present a complete characterization of the tail behavior of the autoregressive Pareto process known as Yeh-Arnold-Robertson Pareto(III) (Yeh et al. [32]). We shall see that it is quite similar to the first order...
On the Individual Moving Average Inequality.
On the predictability of long-range dependent series.
On the suitability of the internet multimedia storage for steganographic information transfer in MP4 files
The aim of this work is to analyze suitability of existing internet multimedia storage services to use as a covert (steganographic) transmission channel. After general overview we focus specifically on the YouTube service. In particular, we study the feasibility of the recently proposed new steganographic technique [6] of hiding information directly in the structure of the mp4-encoded video file. Our statistical analysis of the set of 1000 video files stored by this service show the practical limitations...
On threshold autoregressive processes
On transformations of multivariate ARMA processes
On unequally spaced AR(1) process
Discrete autoregressive process of the first order is considered. The process is observed at unequally spaced time instants. Both least squares estimate and maximum likelihood estimate of the autocorrelation coefficient are analyzed. We show some dangers related with the estimates when the true value of the autocorrelation coefficient is small. Monte-Carlo method is used to illustrate the problems.
One Case of Reduction of Nonlinear Regression to Linear
One prediction of autoregressive time series
Optimising prediction error among completely monotone covariance sequences.