Displaying similar documents to “Discrimination between nonstationary and nearly nonstationary processes, and its effect on forecasting”

Branching processes and models of epidemics

R. Bartoszyński

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CONTEXTS0. Introduction.......................................................................................................................................................................... 5Part IMODELS OF EPIDEMICS FOli INFECTIOUS DISEASES1. Informal description of the phenomenon of epidemics and constructionof mathematical models...........................................................................................................................................................

On invertibility of a random coefficient moving average model

Tomáš Marek (2005)

Kybernetika

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A linear moving average model with random coefficients (RCMA) is proposed as more general alternative to usual linear MA models. The basic properties of this model are obtained. Although some model properties are similar to linear case the RCMA model class is too general to find general invertibility conditions. The invertibility of some special examples of RCMA(1) model are investigated in this paper.

Prediction problems related to a first-order autoregressive process in the presence of outliers

Sugata Sen Roy, Sourav Chakraborty (2006)

Applicationes Mathematicae

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Outliers in a time series often cause problems in fitting a suitable model to the data. Hence predictions based on such models are liable to be erroneous. In this paper we consider a stable first-order autoregressive process and suggest two methods of substituting an outlier by imputed values and then predicting on the basis of it. The asymptotic properties of both the process parameter estimators and the predictors are also studied.

Hazard rate model and statistical analysis of a compound point process

Petr Volf (2005)

Kybernetika

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A stochastic process cumulating random increments at random moments is studied. We model it as a two-dimensional random point process and study advantages of such an approach. First, a rather general model allowing for the dependence of both components mutually as well as on covariates is formulated, then the case where the increments depend on time is analyzed with the aid of the multiplicative hazard regression model. Special attention is devoted to the problem of prediction of process...