Results 21 to 30 of about 96,433 (236)
Time-varying coefficient estimation in the presence of non-stationarity
, 2009 Time-varying coefficient (TVC) estimation is a technique that has been developed to produce consistent estimates of parameters in the simultaneous face of measurement errors, unknown functional form and omitted variables.
P. A. V. B. Swamy (7591415) +3 more
core +6 more sources
Prediction of fatal accidents in Indian factories based on ARIMA
Production Engineering Archives, 2018 The inherent benefits of an accident prevention program are generally known only after an accident has occurred. The purpose of implementation of the program is to minimize the number of accidents and cost of damages. Allocation of resources to implement
SVS Rajaprasad
doaj +1 more source
PEMODELAN JUMLAH KASUS DEMAM BERDARAH DENGUE DENGAN MENGGUNAKAN MODEL AUTOREGRESSIVE DISTRIBUTED LAG
Jurnal Lebesgue, 2023 This study aims to model dengue hemorrhagic fever (DHF) cases with an autoregressive distributed lag (ARDL) model to investigate significant predictor variables in Bojonegoro Regency.
Denny Nurdiansyah, Agus Sulistiawan
doaj +1 more source
Is There A Stable Long-run Relationship Between Unemployment And Productivity?
Comparative Economic Research, 2015 This paper assesses whether productivity and unemployment have a stable long-run relationship. We explore a panel of 19 OECD countries between 1970 and 2012 and rely on recently developed time series econometric methods.
João Tovar Jalles
doaj +1 more source
Learning to Optimize under Non-Stationarity [PDF]
International Conference on Artificial Intelligence and Statistics, 2018 We introduce algorithms that achieve state-of-the-art \emph{dynamic regret} bounds for non-stationary linear stochastic bandit setting. It captures natural applications such as dynamic pricing and ads allocation in a changing environment. We show how the
Wang Chi Cheung +2 more
semanticscholar +1 more source
Hedging the Drift: Learning to Optimize under Non-Stationarity [PDF]
Management Sciences, 2019 We introduce data-driven decision-making algorithms that achieve state-of-the-art dynamic regret bounds for a collection of nonstationary stochastic bandit settings.
Wang Chi Cheung +2 more
semanticscholar +1 more source
Monitoring Stationarity and Cointegration [PDF]
SSRN Electronic Journal, 2015 We propose a monitoring procedure to detect a structural change from stationary to integrated behavior. When the procedure is applied to the residuals of a relationship between integrated series it thus monitors a structural change from a cointegrating relationship to a spurious relationship. The cointegration monitoring procedure is based on residuals
Wagner, Martin, Wied, Dominik
openaire +4 more sources
The Taylor Property in Bilinear Models
Revstat Statistical Journal, 2015 The aim of this paper is to discuss the presence of the Taylor property in the class of simple bilinear models. Considering strictly and weakly stationary models, we deduce autocorrelations of the process and of its square and analyze the presence of ...
E. Gonçalves +2 more
doaj +1 more source
Stationarization via surrogates [PDF]
Journal of Statistical Mechanics: Theory and Experiment, 2009 The surrogate data method, classically used for non-linearity tests, amounts to the use of some constrained noise providing a reference for statistical testing. It is revisited here as a method for stationarization and this feature is put forward in the context of non-stationarity testing.
Borgnat, Pierre, Flandrin, Patrick
openaire +1 more source
Revista Brasileira de Engenharia Agrícola e Ambiental, 2012 No Brasil, a região do Distrito Federal é caracterizada pela presença de córregos e pequenos rios, o que torna importante a caracterização das vazões em microbacias.
Fernanda A. O. de Souza +3 more
doaj +1 more source