On discrete sampling of time-varying continuous-time systems
Robinson, Peter M.
On discrete sampling of time-varying continuous-time systems by Peter M. Robinson - Econometric Theory Volume 25, number 4 .
We consider a multivariate continuous-time process, generated by a system of linear stochastic differential equations, driven by white noise, and involving coefficients that possibly vary over time. The process is observable only at discrete, but not necessarily equally-spaced, time points (though equal spacing significantly simplifies matters). Such settings represent partial extensions of ones studied extensively by A.R. Bergstrom. A model for the observed time series is deduced. Initially we focus on a first-order model, but higher-order models are discussed in the case of equally-spaced observations. Some discussion of issues of statistical inference is included
Stochastic process
HB139.T52 ECO
On discrete sampling of time-varying continuous-time systems by Peter M. Robinson - Econometric Theory Volume 25, number 4 .
We consider a multivariate continuous-time process, generated by a system of linear stochastic differential equations, driven by white noise, and involving coefficients that possibly vary over time. The process is observable only at discrete, but not necessarily equally-spaced, time points (though equal spacing significantly simplifies matters). Such settings represent partial extensions of ones studied extensively by A.R. Bergstrom. A model for the observed time series is deduced. Initially we focus on a first-order model, but higher-order models are discussed in the case of equally-spaced observations. Some discussion of issues of statistical inference is included
Stochastic process
HB139.T52 ECO