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Estimation of a time series model from unequally spaced data


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  • Robinson, P. M.
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    A process generated by a stochastic differential equation driven by pure noise is sampled at irregular intervals. A model for the sampled sequence is deduced. We describe a maximum likelihood procedure for estimating the parameters and establish the strong consistency and asymptotic normality of the estimates. The use of the model in prediction is considered. Simplifications in the case of periodic sampling are explored.

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    Bibliographic Info

    Article provided by Elsevier in its journal Stochastic Processes and their Applications.

    Volume (Year): 6 (1977)
    Issue (Month): 1 (November)
    Pages: 9-24

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    Handle: RePEc:eee:spapps:v:6:y:1977:i:1:p:9-24

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    Cited by:
    1. Robinson, P.M., 2008. "Correlation testing in time series, spatial and cross-sectional data," Journal of Econometrics, Elsevier, vol. 147(1), pages 5-16, November.
    2. Peter Robinson, 2007. "On discrete sampling of time-varying continuous-time systems," LSE Research Online Documents on Economics 6795, London School of Economics and Political Science, LSE Library.
    3. Peter Robinson, 2008. "Correlation testing in time series, spatial and cross-sectional data," LSE Research Online Documents on Economics 25470, London School of Economics and Political Science, LSE Library.
    4. Oscar Jorda & Massimiliano Marcellino, 2003. "Stochastic Processes Subject To Time Scale Transformations: An Application To High-Frequency Fx Data," Working Papers 02, University of California, Davis, Department of Economics.
    5. P. Thomson, 1992. "Signal estimation using stochastic velocity models and irregular arrays," Annals of the Institute of Statistical Mathematics, Springer, vol. 44(1), pages 13-25, March.
    6. Miguel A. Delgado & Peter M Robinson, 2013. "Non-Nested Testing of Spatial Correlation," STICERD - Econometrics Paper Series /2013/568, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    7. Peter Robinson, 2007. "Correlation testing in time series, spatial and cross-sectional data," CeMMAP working papers CWP01/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Yacine Ait-Sahalia & Per A. Mykland, 2002. "The Effects of Random and Discrete Sampling When Estimating Continuous-Time Diffusions," NBER Technical Working Papers 0276, National Bureau of Economic Research, Inc.
    9. Vilar, José A. & Vilar, Juan M., 2000. "Finite sample performance of density estimators from unequally spaced data," Statistics & Probability Letters, Elsevier, vol. 50(1), pages 63-73, October.
    10. Peter Robinson, 2007. "On Discrete Sampling Of Time-Varyingcontinuous-Time Systems," STICERD - Econometrics Paper Series /2007/520, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.


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