Estimating Parameters of a Multiplicative Seasonal ARIMA Model Using Prediction Error Method Algorithm
Estimation and testing of cointegration relationships with strongly seasonal monthly data
Estimation de moyennes et fonctions de répartition de suites d'échantillonnage
Estimation de Yule–Walker d'un CAR(p) observé à temps discret
Estimation non paramétrique de la régression par la méthode du noyau : propriété de convergence asymptotiquememt normale indépendante
Estimation of a centrality parameter and random sampling time. I. Necessary conditions for optimality
Estimation of a centrality parameter and random sampling time schemes. II. Applications
Estimation of a Regression Function on a Point Process and its Application to Financial Ruin Risk Forecast
2000 Mathematics Subject Classification: Primary 60G55; secondary 60G25.We estimate a regression function on a point process by the Tukey regressogram method in a general setting and we give an application in the case of a Risk Process. We show among other things that, in classical Poisson model with parameter r, if W is the amount of the claim with finite espectation E(W) = m, Sn (resp. Rn) the accumulated interval waiting time for successive claims (resp. the aggregate claims amount) up to the...
Estimation of parameters in exponential autoregressive models.
This paper discusses the estimation of parameters in second order exponential autoregressive models.
Estimation of parameters of RCA with exponential marginals.
Estimation of the Distribution Function of Noise in Stationary Processes.
Estimation of variances in a heteroscedastic RCA(1) model
The paper concerns with a heteroscedastic random coefficient autoregressive model (RCA) of the form . Two different procedures for estimating or , respectively, are described under the special seasonal behaviour of . For both types of estimators strong consistency and asymptotic normality are proved.
Estimation paramétrique d'un processus de diffusion avec retards
Estimation récursive des paramètres d'un modèle de régression, variant au cours du temps
Estimation semi-paramétrique d'un modèle autorégressif stationnaire multiindice non nécessairement causal
Every continuous first order autoregressive stochastic process is a Gaussian process
EWMA historical volatility estimators
Expolynomial Smoothing of Autocorrelated Time Series.
Exponential smoothing and resampling techniques in time series prediction
Time series analysis deals with records that are collected over time. The objectives of time series analysis depend on the applications, but one of the main goals is to predict future values of the series. These values depend, usually in a stochastic manner, on the observations available at present. Such dependence has to be considered when predicting the future from its past, taking into account trend, seasonality and other features of the data. Some of the most successful forecasting methods are...
Exponential smoothing based on L-estimation
Robust methods similar to exponential smoothing are suggested in this paper. First previous results for exponential smoothing in are generalized using the regression quantiles, including a generalization to more parameters. Then a method based on the classical sign test is introduced that should deal not only with outliers but also with level shifts, including a detection of change points. Properties of various approaches are investigated by means of a simulation study. A real data example is...