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Keyword: nonparametric likelihood;
6 results found.
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Karun Adusumilli, Taisuke Otsu and Chen Qiu
This paper is concerned with inference on finite dimensional parameters in semiparametric moment condition models, where the moment functionals are linear with respect to unknown nuisance functions. By exploiting this li...Read more...
1 December 2020
Karun Adusumilli and Taisuke Otsu
Missing or incomplete outcome data is a ubiquitous problem in biomedical and social sciences. Under the missing at random setup, inverse probability weighting is widely applied to estimate and make inference on the popul...Read more...
30 October 2018
Lorenzo Camponovo, Yukitoshi Matsushita and Taisuke Otsu
This paper develops a new test statistic for parameters defined by moment conditions that exhibits desirable relative error properties for the approximation of tail area probabilities. Our statistic, called the tilted ex...Read more...
13 November 2017
We propose a nonparametric likelihood inference method for the integrated volatility under high frequency financial data. The nonparametric likelihood statistic, which contains the conventional statistics such as empiric...Read more...
15 January 2015
Oliver Linton and Enno Mammen
We investigate a class of semiparametric ARCH(8) models that includes as a special case the partially nonparametric (PNP) model introduced by Engle and Ng (1993) and which allows for both flexible dynamics and flexible f...Read more...
Oliver Linton and Zhijie Xiao
We propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error score function obtained from the residuals of a preliminary nonparametric regression. We show that our...Read more...