Bayesian analysis of contaminated quarter plane moving average modelsVALLEJOS, Ronny O; GARCIA-DONATO, Gonzalo.Journal of statistical computation and simulation (Print). 2006, Vol 76, Num 2, pp 131-147, issn 0094-9655, 17 p.Article

Asymptotic results for spatial ARMA modelsILLIG, Aude; TRUONG-VAN, Benoit.Communications in statistics. Theory and methods. 2006, Vol 35, Num 4-6, pp 671-688, issn 0361-0926, 18 p.Article

Bayesian rules and stochastic models for high accuracy prediction of solar radiationVOYANT, Cyril; DARRAS, Christophe; MUSELLI, Marc et al.Applied energy. 2014, Vol 114, pp 218-226, issn 0306-2619, 9 p.Article

Information transformation in a supply chain: a simulation studyGANG LI; SHOUYANG WANG; HONG YAN et al.Computers & operations research. 2005, Vol 32, Num 3, pp 707-725, issn 0305-0548, 19 p.Article

Modified Gaussian likelihood estimators for ARMA models on ℤ^dDIMITRIOU-FAKALOU, Chrysoula.Stochastic processes and their applications. 2009, Vol 119, Num 12, pp 4149-4175, issn 0304-4149, 27 p.Article

Rate of Convergence to Normality of Estimators in a Random Coefficient ARMA(p, q) ModelSUGATA SEN ROY; BHATTACHARYA, Sankha.Communications in statistics. Theory and methods. 2011, Vol 40, Num 4-6, pp 1081-1092, issn 0361-0926, 12 p.Article

Marginal likelihood and unit rootsFRANCKE, Marc K; DE VOS, Aart F.Journal of econometrics. 2007, Vol 137, Num 2, pp 708-728, issn 0304-4076, 21 p.Article

Time Series Analysis of ENR Construction Cost IndexASHURI, Baabak; JIAN LU.Journal of construction engineering and management. 2010, Vol 136, Num 11, pp 1227-1237, issn 0733-9364, 11 p.Article

Maximum likelihood estimation of linear continuous time long memory processes with discrete time dataTSAI, Henghsiu; CHAN, K. S.Journal of the Royal Statistical Society. Series B, statistical methodology. 2005, Vol 67, pp 703-716, issn 1369-7412, 14 p., 5Article

P-convergence des TRA estimateurs: modèle MA (q) = P-convergence of the TRA estimates: the MA(q) modelBERRAHOU, Nawale; EL HIMDI, Khalid.Comptes rendus. Mathématique. 2002, Vol 335, Num 6, pp 549-552, issn 1631-073XArticle

Prediction intervals based on autoregression forecastsDE LUNA, X.Statistician (London. Print). 2000, Vol 49, Num 1, pp 87-93, issn 0039-0526Article

Forecasting-looking back and forward : Paper to celebrate the 50th anniversary of the Econometrics Institute at the Erasmus University, RotterdamGRANGER, Clive W. J.Journal of econometrics. 2007, Vol 138, Num 1, pp 3-13, issn 0304-4076, 11 p.Article

An application of the TRAMO-SEATS automatic procedure; direct versus indirect adjustmentMARAVALL, Agustin.Computational statistics & data analysis. 2006, Vol 50, Num 9, pp 2167-2190, issn 0167-9473, 24 p.Article

Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time seriesFERGUSON, Jake M; PONCIANO, José M.Ecology letters (Print). 2014, Vol 17, Num 2, pp 251-259, issn 1461-023X, 9 p.Article

A Short-Term Ensemble Wind Speed Forecasting System for Wind Power ApplicationsTRAITEUR, Justin J; CALLICUTT, David J; SMITH, Maxwell et al.Journal of applied meteorology and climatology. 2012, Vol 51, Num 10, pp 1763-1774, issn 1558-8424, 12 p.Article

Séries temporelles = Time seriesARAGON, Yves.Techniques de l'ingénieur. Sciences fondamentales. 2009, Vol AFM3, Num AF614, AF614.1-AF614.23, docAF614.1 [24 p.]Article

A measure of bullwhip effect in supply chains with a mixed autoregressive-moving average demand processTRUONG TON HIEN DUC; HUYNH TRUNG LUONG; KIM, Yeong-Dae et al.European journal of operational research. 2008, Vol 187, Num 1, pp 243-256, issn 0377-2217, 14 p.Article

Low-order model for speech signalsMITICHE, Lahcène; ADAMOU-MITICHE, Amel B. H; BERKANI, Daoud et al.Signal processing. 2004, Vol 84, Num 10, pp 1805-1811, issn 0165-1684, 7 p.Article

Statistical analysis of incomplete long-range dependent dataPALMA, W; DEL PINO, G.Biometrika. 1999, Vol 86, Num 4, pp 965-972, issn 0006-3444Article

Crude oil reserve estimation : an application of the autoregressive integrated moving average (ARIMA) modelAYENI, B. J; PILAT, R.Journal of petroleum science & engineering. 1992, Vol 8, Num 1, pp 13-28, issn 0920-4105Article

Municipal Water Demand Forecasting: Tools for Intervention Time SeriesHERRERA, M; GARCIA-DIAZ, J. C; IZQUIERDO, J et al.Stochastic analysis and applications. 2011, Vol 29, Num 6, pp 998-1007, issn 0736-2994, 10 p.Article

Seasonal fractional ARIMA with stable innovationsKA DIONGUE, Abdou; DIOP, Aliou; NDONGO, Mor et al.Statistics & probability letters. 2008, Vol 78, Num 12, pp 1404-1411, issn 0167-7152, 8 p.Article

Some evidence on forecasting time-series with support vector machinesHANSEN, J. V; MCDONALD, J. B; NELSON, R. D et al.The Journal of the Operational Research Society. 2006, Vol 57, Num 9, pp 1053-1063, issn 0160-5682, 11 p.Article

Application of Wiener series for assessment of the quality of the NARMAX model of dynamic loudspeakersDOBRUCKI, A; PRUCHNICKI, P.Computational and experimental methods. 2003, pp 223-232, issn 1466-7266, isbn 1-85312-975-5, 1Vol, 10 p.Conference Paper

Modeling Identification and Control of Peltier Thermoelectic Modules for TelepresenceGUIATNI, Mohamed; KHEDDAR, Abderrahmane.Journal of dynamic systems, measurement, and control. 2011, Vol 133, Num 3, issn 0022-0434, 031010.1-031010.8Article