Results 41 to 50 of about 6,198,544 (193)

Two-Stage Method Based on Local Polynomial Fitting for a Linear Heteroscedastic Regression Model and Its Application in Economics

Discrete Dynamics in Nature and Society, 2012
We introduce the extension of local polynomial fitting to the linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using ...
Liyun Su, Yanyong Zhao, Tianshun Yan
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Asymptotic Form of the Covariance Matrix of Likelihood-Based Estimator in Multidimensional Linear System Model for the Case of Infinity Number of Nuisance Parameters

Mathematics
This article is devoted to the synthesis and analysis of the quality of the statistical estimate of parameters of a multidimensional linear system (MLS) with one input and m outputs. A nontrivial case is investigated when the one-dimensional input signal
Alexander Varypaev
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Nonparametric testing of lack of dependence in functional linear models.

PLoS ONE, 2020
An important inferential task in functional linear models is to test the dependence between the response and the functional predictor. The traditional testing theory was constructed based on the functional principle component analysis which requires ...
Wenjuan Hu, Nan Lin, Baoxue Zhang
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L 1 $L_{1}$ -Estimation for covariate-adjusted regression

Journal of Inequalities and Applications, 2020
We study a covariate-adjusted regression(CAR) model that is proposed for such situations where both predictors and response in a regression model are not directly observable but are distorted by a multiplicative factor that is determined by an unknown ...
Yaodong Sun, Dehui Wang
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The local asymptotic normality of pointed processes. [PDF]

, 2012
The purpose of this work is to determine general conditions for local asymptotic normality to be assured.The point processes (renewal process and non-homogenous Poisson process) and their properties are examined in the first part of work.
Tarasova, Darja,
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Robust-BD Estimation and Inference for General Partially Linear Models

Entropy, 2017
The classical quadratic loss for the partially linear model (PLM) and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD)” estimators of both the parametric
Chunming Zhang, Zhengjun Zhang
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Empirical Lossless Compression Bound of a Data Sequence

Entropy
We consider the lossless compression bound of any individual data sequence. Conceptually, its Kolmogorov complexity is such a bound yet uncomputable. According to Shannon’s source coding theorem, the average compression bound is nH, where n is the number
Lei M. Li
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Calibration for Computer Models with Time-Varying Parameter

Mathematics
Traditional calibration methods often assume constant parameters that remain unchanged across input conditions, which can limit predictive accuracy when parameters actually vary.
Yang Sun, Xiangzhong Fang
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Gamma Kernel Estimators for Density and Hazard Rate of Right-Censored Data

Journal of Probability and Statistics, 2011
The nonparametric estimation for the density and hazard rate functions for right-censored data using the kernel smoothing techniques is considered. The “classical” fixed symmetric kernel type estimator of these functions performs well in the interior ...
T. Bouezmarni, A. El Ghouch, M. Mesfioui
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An Alternative Asymptotic Analysis of Residual-Based Statistics [PDF]

This paper presents an alternative method to derive the limiting distribution of residual-based statistics. Our method does not impose an explicit assumption of (asymptotic) smoothness of the statistic of interest with respect to the model's parameters ...
Bas J.M. Werker, Elena Andreou
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