Results 31 to 40 of about 91,156 (303)
Pseudo-Gaussian and Rank-Based Tests for First-Order Superdiagonal Bilinear Models in Panel Data
Revstat Statistical Journal, 2021 In this paper, locally asymptotically optimal (in the H´ajek-Le Cam sense) parametric, pseudo-Gaussian and rank-based procedures are proposed for the problem of testing randomness against first-order superdiagonal bilinear panel dependence (in large n ...
Aziz Lmakri +3 more
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Fisher informations and local asymptotic normality for continuous-time quantum Markov processes [PDF]
, 2014 We consider the problem of estimating an arbitrary dynamical parameter of an open quantum system in the input–output formalism. For irreducible Markov processes, we show that in the limit of large times the system-output state can be approximated by a ...
C. Cătană, L. Bouten, M. Guţă
semanticscholar +1 more source
Efficient Estimation in Heteroscedastic Varying Coefficient Models
Econometrics, 2015 This paper considers statistical inference for the heteroscedastic varying coefficient model. We propose an efficient estimator for coefficient functions that is more efficient than the conventional local-linear estimator.
Chuanhua Wei, Lijie Wan
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Integral Least-Squares Inferences for Semiparametric Models with Functional Data
Journal of Applied Mathematics, 2014 The inferences for semiparametric models with functional data are investigated. We propose an integral least-squares technique for estimating the parametric components, and the asymptotic normality of the resulting integral least-squares estimator is ...
Limian Zhao, Peixin Zhao
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Local asymptotic normality and efficient estimation for multivariate GINAR(p) models
Cogent Mathematics & Statistics, 2019 We derive the Local Asymptotic Normality (LAN) property for a multivariate generalized integer-valued autoregressive (MGINAR) process with order p. The generalized thinning operator in the MGINAR(p) process includes not only the usual Binomial thinning ...
Hiroshi Shiraishi
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Discrete Dynamics in Nature and Society, 2021 In this paper, we focus on heteroscedastic partially linear varying-coefficient errors-in-variables models under right-censored data with censoring indicators missing at random.
Yuye Zou, Chengxin Wu
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The Local Linear M-Estimation with Missing Response Data
Journal of Applied Mathematics, 2014 This paper studies the nonparametric regressive function with missing response data. Three local linear M-estimators with the robustness of local linear regression smoothers are presented such that they have the same asymptotic normality and consistency.
Shuanghua Luo +2 more
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Asymptotic estimation for statistical models of continuous-time discrete martingales
Lietuvos Matematikos RinkinysThe paper deals with statistical experiments of the continuous-time discrete local martingales, including models of all types of point processes. The process of local density of the discrete local martingales is expressed by a stochastic exponent of the
Vaidotas Kanišauskas +1 more
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Variable bandwidth local maximum likelihood type estimation for diffusion processes
Advances in Difference Equations, 2018 The method of robust approach is applied to estimate drift function and diffusion function of diffusion processes with discrete-time observations. The proposed method combines the ideas of local linear regression technique and maximum likelihood type ...
Ming T. Tang, Yun Y. Wang
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Expectile Regression on Distributed Large-Scale Data
IEEE Access, 2020 Large-scale data presents great challenges to data analysis due to the limited computer storage capacity and the heterogeneous data structure. In this article, we propose a distributed expectile regression model to resolve the challenges of large-scale ...
Aijun Hu, Chujin Li, Jing Wu
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