Statistical inference for discrete-time samples from affine stochastic delay differential equations

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Standard

Statistical inference for discrete-time samples from affine stochastic delay differential equations. / Küchler, Uwe; Sørensen, Michael.

I: Bernoulli, Bind 19, Nr. 2, 2013, s. 409 - 425.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Küchler, U & Sørensen, M 2013, 'Statistical inference for discrete-time samples from affine stochastic delay differential equations', Bernoulli, bind 19, nr. 2, s. 409 - 425. https://doi.org/10.3150/11-BEJ411

APA

Küchler, U., & Sørensen, M. (2013). Statistical inference for discrete-time samples from affine stochastic delay differential equations. Bernoulli, 19(2), 409 - 425. https://doi.org/10.3150/11-BEJ411

Vancouver

Küchler U, Sørensen M. Statistical inference for discrete-time samples from affine stochastic delay differential equations. Bernoulli. 2013;19(2):409 - 425. https://doi.org/10.3150/11-BEJ411

Author

Küchler, Uwe ; Sørensen, Michael. / Statistical inference for discrete-time samples from affine stochastic delay differential equations. I: Bernoulli. 2013 ; Bind 19, Nr. 2. s. 409 - 425.

Bibtex

@article{0270d6c39ed44c7db3ae0c1c24995d27,
title = "Statistical inference for discrete-time samples from affine stochastic delay differential equations",
abstract = "Statistical inference for discrete time observations of an affine stochastic delay differential equation is considered. The main focus is on maximum pseudo-likelihood estimators, which are easy to calculate in practice. A more general class of prediction-based estimating functions is investigated as well. In particular, the optimal prediction-based estimating function and the asymptotic properties of the estimators are derived. The maximum pseudo-likelihood estimator is a particular case, and an expression is found for the efficiency loss when using the maximum pseudo-likelihood estimator, rather than the computationally more involved optimal prediction-based estimator. The distribution of the pseudo-likelihood estimator is investigated in a simulation study. Two examples of affine stochastic delay equation are considered in detail. ",
author = "Uwe K{\"u}chler and Michael S{\o}rensen",
year = "2013",
doi = "10.3150/11-BEJ411",
language = "English",
volume = "19",
pages = "409 -- 425",
journal = "Bernoulli",
issn = "1350-7265",
publisher = "International Statistical Institute",
number = "2",

}

RIS

TY - JOUR

T1 - Statistical inference for discrete-time samples from affine stochastic delay differential equations

AU - Küchler, Uwe

AU - Sørensen, Michael

PY - 2013

Y1 - 2013

N2 - Statistical inference for discrete time observations of an affine stochastic delay differential equation is considered. The main focus is on maximum pseudo-likelihood estimators, which are easy to calculate in practice. A more general class of prediction-based estimating functions is investigated as well. In particular, the optimal prediction-based estimating function and the asymptotic properties of the estimators are derived. The maximum pseudo-likelihood estimator is a particular case, and an expression is found for the efficiency loss when using the maximum pseudo-likelihood estimator, rather than the computationally more involved optimal prediction-based estimator. The distribution of the pseudo-likelihood estimator is investigated in a simulation study. Two examples of affine stochastic delay equation are considered in detail.

AB - Statistical inference for discrete time observations of an affine stochastic delay differential equation is considered. The main focus is on maximum pseudo-likelihood estimators, which are easy to calculate in practice. A more general class of prediction-based estimating functions is investigated as well. In particular, the optimal prediction-based estimating function and the asymptotic properties of the estimators are derived. The maximum pseudo-likelihood estimator is a particular case, and an expression is found for the efficiency loss when using the maximum pseudo-likelihood estimator, rather than the computationally more involved optimal prediction-based estimator. The distribution of the pseudo-likelihood estimator is investigated in a simulation study. Two examples of affine stochastic delay equation are considered in detail.

U2 - 10.3150/11-BEJ411

DO - 10.3150/11-BEJ411

M3 - Journal article

VL - 19

SP - 409

EP - 425

JO - Bernoulli

JF - Bernoulli

SN - 1350-7265

IS - 2

ER -

ID: 44916560