A review of asymptotic theory of estimating functions
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A review of asymptotic theory of estimating functions. / Jacod, Jean ; Sørensen, Michael.
In: Statistical Inference for Stochastic Processes, Vol. 21, No. 2, 2018, p. 415-434.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - A review of asymptotic theory of estimating functions
AU - Jacod, Jean
AU - Sørensen, Michael
PY - 2018
Y1 - 2018
N2 - Asymptotic statistical theory for estimating functions is reviewed in a generalitysuitable for stochastic processes. Conditions concerning existence of a consistent estimator,uniqueness, rate of convergence, and the asymptotic distribution are treated separately. Ourconditions are not minimal, but can be verified for many interesting stochastic processmodels.Several examples illustrate the wide applicability of the theory and why the generality isneeded.
AB - Asymptotic statistical theory for estimating functions is reviewed in a generalitysuitable for stochastic processes. Conditions concerning existence of a consistent estimator,uniqueness, rate of convergence, and the asymptotic distribution are treated separately. Ourconditions are not minimal, but can be verified for many interesting stochastic processmodels.Several examples illustrate the wide applicability of the theory and why the generality isneeded.
U2 - 10.1007/s11203-018-9178-8
DO - 10.1007/s11203-018-9178-8
M3 - Journal article
VL - 21
SP - 415
EP - 434
JO - Statistical Inference for Stochastic Processes
JF - Statistical Inference for Stochastic Processes
SN - 1387-0874
IS - 2
ER -
ID: 200179384