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zadetkov: 150
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  • James-Stein Type Center Pix... James-Stein Type Center Pixel Weights for Non-Local Means Image Denoising
    Yue Wu; Tracey, B.; Natarajan, P. ... IEEE signal processing letters, 04/2013, Letnik: 20, Številka: 4
    Journal Article
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    Odprti dostop

    Non-Local Means (NLM) and its variants have proven to be effective and robust in many image denoising tasks. In this letter, we study approaches to selecting center pixel weights (CPW) in NLM. Our ...
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2.
  • On homogeneous James–Stein ... On homogeneous James–Stein type estimators
    Boukehil, Djamila; Fourdrinier, Dominique; Mezoued, Fatiha ... Statistics & probability letters, December 2022, 2022-12-00, Letnik: 191
    Journal Article
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    The shrinkage factor of the James–Stein estimators of a multivariate normal involves the power of the squared norm of X. We show powers of the norm greater than 2 also give improvement, while lesser ...
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3.
  • Multivariate control charts... Multivariate control charts based on the James–Stein estimator
    Wang, Hsiuying; Huwang, Longcheen; Yu, Jeng Hung European journal of operational research, 10/2015, Letnik: 246, Številka: 1
    Journal Article
    Recenzirano

    •Multivariate control chart is a useful tool in quality control.•We use the James–Stein estimator to construct better control charts.•JS-type control charts are proposed. In this study, we focus on ...
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4.
  • Simultaneous confidence reg... Simultaneous confidence regions for multivariate bioequivalence
    Pallmann, Philip; Jaki, Thomas Statistics in medicine, 20 December 2017, Letnik: 36, Številka: 29
    Journal Article
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    Demonstrating bioequivalence of several pharmacokinetic (PK) parameters, such as AUC and Cmax, that are calculated from the same biological sample measurements is in fact a multivariate problem, even ...
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5.
  • On the James-Stein estimato... On the James-Stein estimator for the poisson regression model
    Amin, Muhammad; Akram, Muhammad Nauman; Amanullah, Muhammad Communications in statistics. Simulation and computation, 10/2022, Letnik: 51, Številka: 10
    Journal Article
    Recenzirano

    The Poisson regression model (PRM) aims to model a counting variable y, which is usually estimated by using maximum likelihood estimation (MLE) method. The performance of MLE is not satisfactory in ...
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  • Performance of some estimat... Performance of some estimators for the multicollinear logistic regression model: theory, simulation, and applications
    Hoque, Md Ariful; Kibria, B. M. Golam Research in statistics (Philadelphia, Pa.), 12/2024, Letnik: 2, Številka: 1
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    This article proposes some new estimators, namely Stein’s estimators for ridge regression and Kibria and Lukman estimator and compares their performance with some existing estimators, namely maximum ...
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  • Bounded Self-Weights Estima... Bounded Self-Weights Estimation Method for Non-Local Means Image Denoising Using Minimax Estimators
    Nguyen, Minh Phuong; Chun, Se Young IEEE transactions on image processing, 2017-April, 2017-Apr, 2017-4-00, 20170401, Letnik: 26, Številka: 4
    Journal Article
    Recenzirano
    Odprti dostop

    A non-local means (NLM) filter is a weighted average of a large number of non-local pixels with various image intensity values. The NLM filters have been shown to have powerful denoising performance, ...
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9.
  • Estimation of the drift of ... Estimation of the drift of Riemann-Liouville fractional Brownian motion
    Fatima-Ezzahra, Farah Communications in statistics. Theory and methods, 07/2023, Letnik: 52, Številka: 13
    Journal Article
    Recenzirano

    We consider the problem of efficient estimation of the drift of Riemann-Liouville fractional Brownian motion with Hurst parameter H less than We also construct superefficient James-Stein type ...
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  • Stein estimators for the dr... Stein estimators for the drift of the mixing of two fractional Brownian motions
    Djerfi, Kouider; Djellouli, Ghaouti; Madani, Fethi Communications in statistics. Theory and methods, 03/2024, Letnik: 53, Številka: 6
    Journal Article
    Recenzirano

    In this paper, we consider the problem of efficient estimation for the drift parameter θ ∈ R d in the linear model Z t : = θ t + σ 1 B H 1 ( t ) + σ 2 B H 2 ( t ) , t ∈ 0 , T . Where B H 1 and B H ...
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zadetkov: 150

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