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IMPROVED SEMI-PARAMETRIC TIME SERIES MODELS OF AIR POLLUTION AND MORTALITY
Semiparametric regression time series Particulate Matter (PM) Generalized Additive Model Generalized Linear Model Mean Squared Error Bandwidth Selection
2015/8/21
In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders conce...
Approximate Inference for Observation Driven Time Series Models with Intractable Likelihoods
Observation Driven Time Series Models Approximate Bayesian Computation Asymptotic Con-sistency Markov Chain Monte Carlo
2013/4/28
In the following article we consider approximate Bayesian parameter inference for observation driven time series models. Such statistical models appear in a wide variety of applications, including eco...
This paper is a note on the use of Bayesian nonparametric mixture models for continuous time series. We identify a key requirement for such models, and then establish that there is a single type of mo...
Multi-Scale and Hidden Resolution Time Series Models
Autoregressive models Bayesian inference Combination of multiresolution information Jerey rule of conditioning
2009/9/21
We introduce a class of multi-scale models for time series. The novel framework couples standard linear models at dierent levels of resolution via stochastic links across scales. Jerey rule of conditi...
Estimation in a class of nonlinear heteroscedastic time series models
Conditional least-squares estimation Conditional likelihood estimation Heteroscedastic models Kernel density estimation LATEX2ε
2009/9/16
Parameter estimation in a class of heteroscedastic time series models is investigated. The existence of conditional least-squares and conditional likelihood estimators is proved. Their consistency and...