Results 41 to 50 of about 6,008,196 (338)
Maximum likelihood estimation for Gaussian process with nonlinear drift
Nonlinear Analysis, 2018 We investigate the regression model Xt = θG(t) + Bt, where θ is an unknown parameter, G is a known nonrandom function, and B is a centered Gaussian process.
Yuliya Mishura +2 more
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Entropy, 2020 High-dimensional variable selection is an important research topic in modern statistics. While methods using nonlocal priors have been thoroughly studied for variable selection in linear regression, the crucial high-dimensional model selection properties
Xuan Cao, Kyoungjae Lee
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Parameter estimation for fractional mixed fractional Brownian motion based on discrete observations
Modern Stochastics: Theory and Applications, 2023 The object of investigation is the mixed fractional Brownian motion of the form ${X_{t}}=\kappa {B_{t}^{{H_{1}}}}+\sigma {B_{t}^{{H_{2}}}}$, driven by two independent fractional Brownian motions ${B_{1}^{H}}$ and ${B_{2}^{H}}$ with Hurst parameters ${H_ ...
Kostiantyn Ralchenko, Mykyta Yakovliev
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Strong consistency of a kernel-based rule for spatially dependent data [PDF]
Arab Journal of Mathematical Sciences, 2020 We consider the kernel-based classifier proposed by Younso (2017). This nonparametric classifier allows for the classification of missing spatially dependent data. The weak consistency of the classifier has been studied by Younso (2017).
Ahmad Younso, Ziad Kanaya, Nour Azhari
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On strong consistency of the variance estimator [PDF]
Proceedings of the 19th conference on Winter simulation - WSC '87, 1987 One way to construct a confidence interval for the mean constant of a stochastic process, is via consistent estimation of another parameter of the process, namely, the time-average variance constant. In this paper, we discuss strong consistency of the variance estimator for several methods of steady-state output analysis.
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Strong Consistency of Incomplete Functional Percentile Regression
AxiomsThis paper analyzes the co-fluctuation between a scalar response random variable and a curve regressor using quantile regression. We focus on the situation wherein the output variable is observed with random missing.
Mohammed B. Alamari +3 more
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Some Asymptotic Results of Kernel Density Estimator in Length-Biased Sampling [PDF]
Journal of Sciences, Islamic Republic of Iran, 2013 In this paper, we prove the strong uniform consistency and asymptotic normality of the kernel density estimator proposed by Jones [12] for length-biased data.The approach is based on the invariance principle for the empirical processes proved by Horváth [
M. Ajami, V. Fakoor, S. Jomhoori
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Asymptotic Properties of Parameter Estimators in Fractional Vasicek Model
Lithuanian Journal of Statistics, 2016 We consider the fractional Vasicek model of the form dXt = (α-βXt)dt + γdBHt, driven by fractional Brownian motion BH with Hurst parameter H ∈ (0,1). We construct three estimators for an unknown parameter θ=(α,β) and prove their strong consistency.
Stanislav Lohvinenko +2 more
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Quasi-maximum likelihood estimator of Laplace (1, 1) for GARCH models
Open Mathematics, 2017 This paper studies the quasi-maximum likelihood estimator (QMLE) for the generalized autoregressive conditional heteroscedastic (GARCH) model based on the Laplace (1,1) residuals.
Xuan Haiyan +3 more
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Strong consistency of multivariate spectral variance estimators in Markov chain Monte Carlo
Bernoulli, 2015 Markov chain Monte Carlo (MCMC) algorithms are used to estimate features of interest of a distribution. The Monte Carlo error in estimation has an asymptotic normal distribution whose multivariate nature has so far been ignored in the MCMC community.
Dootika Vats +2 more
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