TY  - CHAP
AB  - Many economic and business problems require a set of random variates from the posterior density of the unknown parameters. The set of random variates can be used to integrate numerically many forms of functions. Since a closed form of the posterior density of models in time series analysis is not usually well known, it is not easy to generate a set of random variates. As a sampling scheme based on the probabilities proportional to sizes of the sample space, sampling importance resampling (SIR) method can be applied to generate a set of random variates from the posterior density. Application of SIR to signal extraction model of time series analysis is illustrated and given a set of random variates, the procedures to compute the Monte Carlo estimator of the component of signal extraction model are discussed. The procedures are illustrated with simulated data.
VL  - 5
SN  - 978-0-85724-787-2, 978-0-7623-1478-2/1477-4070
DO  - 10.1016/S1477-4070(07)00215-2
UR  - https://doi.org/10.1016/S1477-4070(07)00215-2
AU  - Lee Jae J.
ED  - Kenneth D. Lawrence
ED  - Michael D. Geurts
PY  - 2008
Y1  - 2008/01/01
TI  - Applying resampling scheme to time series analysis
T2  - Advances in Business and Management Forecasting
T3  - Advances in Business and Management Forecasting
PB  - Emerald Group Publishing Limited
SP  - 267
EP  - 279
Y2  - 2024/04/16
ER  -