Prediction-based estimating functions: Review and new developments
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Prediction-based estimating functions: Review and new developments. / Sørensen, Michael.
I: Brazilian Journal of Probability and Statistics, Bind 25, Nr. 3, 2011, s. 362-391.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Prediction-based estimating functions: Review and new developments
AU - Sørensen, Michael
PY - 2011
Y1 - 2011
N2 - The general theory of prediction-based estimating functions for stochastic process models is reviewed and extended. Particular attention is given to optimal estimation, asymptotic theory and Gaussian processes. Several examples of applications are presented. In particular, partial observation of a system of stochastic differential equations is discussed. This includes diffusions observed with measurement errors, integrated diffusions, stochastic volatility models, and hypoelliptic stochastic differential equations. The Pearson diffusions, for which explicit optimal prediction-based estimating functions can be found, are briefly presented.
AB - The general theory of prediction-based estimating functions for stochastic process models is reviewed and extended. Particular attention is given to optimal estimation, asymptotic theory and Gaussian processes. Several examples of applications are presented. In particular, partial observation of a system of stochastic differential equations is discussed. This includes diffusions observed with measurement errors, integrated diffusions, stochastic volatility models, and hypoelliptic stochastic differential equations. The Pearson diffusions, for which explicit optimal prediction-based estimating functions can be found, are briefly presented.
M3 - Journal article
VL - 25
SP - 362
EP - 391
JO - Brazilian Journal of Probability and Statistics
JF - Brazilian Journal of Probability and Statistics
SN - 0103-0752
IS - 3
ER -
ID: 34253429