Local Asymptotic Normality and Efficient Estimation for INAR(p) Models [PDF]
SSRN Electronic Journal, 2006 Abstract. Integer‐valued autoregressive (INAR) processes have been introduced to model non‐negative integer‐valued phenomena that evolve in time. The distribution of an INAR(p) process is determined by two parameters: a vector of survival probabilities and a probability distribution on the non‐negative integers, called an immigration distribution ...
Drost, F.C. +2 more
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Local asymptotic normality in a stationary model for spatial extremes [PDF]
Journal of Multivariate Analysis, 2011 \textit{L. De Haan} and \textit{T. Pereira}, [Spatial extremes: models for the stationary case. Ann. Stat. 34, No. 1, 146--168 (2006; Zbl 1104.60021)] provided models for spatial extremes in the case of stationarity which depend on just one parameter \(\beta>0\) measuring tail dependence, and proposed different estimators for this parameter.
Falk, Michael, Michael Falk
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Generalized Partially Functional Linear Model with Unknown Link Function
Axioms, 2023 In existing models with an unknown link function, the issue of predictors containing both multiple functional data and multiple scalar data has not been studied. To fill this gap, we propose a generalized partially functional linear model, which not only
Weiwei Xiao, Songxuan Li, Haiyan Liu
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Local asymptotic normality for qubit states [PDF]
Physical Review A, 2006 16 pages, 3 figures, published ...
Guta, M.I., Kahn, J.
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Asymptotically Normal Estimation of Local Latent Network Curvature
CoRR, 2022 Network data, commonly used throughout the physical, social, and biological sciences, consist of nodes (individuals) and the edges (interactions) between them. One way to represent network data's complex, high-dimensional structure is to embed the graph into a low-dimensional geometric space.
Steven Wilkins-Reeves +1 more
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GMM Estimation of a Partially Linear Additive Spatial Error Model
Mathematics, 2021 This article presents a partially linear additive spatial error model (PLASEM) specification and its corresponding generalized method of moments (GMM).
Jianbao Chen, Suli Cheng
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Consistency and Asymptotic Normality of Estimator for Parameters in Multiresponse Multipredictor Semiparametric Regression Model [PDF]
, 2022 A multiresponse multipredictor semiparametric regression (MMSR) model is a combi-nation of parametric and nonparametric regressions models with more than one predictor and response variables where there is correlation between responses.
Nur Chamidah, S.Si., M.Si +2 more
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Consistency and asymptotic normality of the maximum likelihood estimator in a zero-inflated generalized Poisson regression [PDF]
, 2005 Poisson regression models for count variables have been utilized in many applications. However, in many problems overdispersion and zero-inflation occur.
Min, Aleksey, Czado, Claudia
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Wavelet-M-Estimation for Time-Varying Coefficient Time Series Models
Discrete Dynamics in Nature and Society, 2020 This paper proposes wavelet-M-estimation for time-varying coefficient time series models by using a robust-type wavelet technique, which can adapt to local features of the time-varying coefficients and does not require the smoothness of the unknown time ...
Xingcai Zhou, Fangxia Zhu
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Local limit theorem for coefficients of modified Borwein’s algorithm, proved by the ratio method
Lietuvos Matematikos Rinkinys, 2019 The paper continues the research of the modified Borwein method for the evaluation of the Riemann zeta-function. It provides a different perspective on the derivation of the local limit theorem for coefficients of the method.
Igoris Belovas
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