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    A Survey of Sampling Methods for Hyperspectral Remote Sensing: Addressing Bias Induced by Random Sampling by Kevin T. Decker, Brett J. Borghetti

    Published 2025-04-01
    “…Identified as early as 2000, the challenges involved in developing and assessing remote sensing models with small datasets remain, with one key issue persisting: the misuse of random sampling to generate training and testing data. …”
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    Bounds of random star discrepancy for HSFC-based sampling by Xiaoda Xu

    Published 2025-03-01
    “…This paper is dedicated to the estimation of the probabilistic upper bounds of star discrepancy for Hilbert's space filling curve (HSFC) sampling. The primary concept revolves around the stratified random sampling method, with the relaxation of the stringent requirement for a sampling number $ N = m^d $ in jittered sampling. …”
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    Stabilization for Networked Control Systems with Random Sampling Periods by Yuan Li, Qingling Zhang, Shuanghong Zhang, Min Cai

    Published 2013-01-01
    “…This paper investigates the stabilization of networked control systems (NCSs) with random delays and random sampling periods. Sampling periods can randomly switch between three cases according to the high, low, and medium types of network load. …”
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    Variance Reduction Optimization Algorithm Based on Random Sampling by GUO Zhenhua, YAN Ruidong, QIU Zhiyong, ZHAO Yaqian, LI Rengang

    Published 2025-03-01
    “…The main feature of the algorithm including an inner and outer double loop structure is designed: the outer loop structure uses mini-batch random samples to calculate the gradient, approximating the full gradient and reducing the gradient calculation cost; the inner loop structure also uses mini-batch random samples to calculate the gradient and replace the single sample random gradient, improving convergence stability of the algorithm. …”
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    New adjusted missing value imputation in multiple regression with simple random sampling and rank set sampling methods. by Juthaphorn Sinsomboonthong, Saichon Sinsomboonthong

    Published 2025-01-01
    “…The four imputation methods were the following: regression-ratio quartile1,3 (R-RQ1,3) imputation of Al-Omari, Jemain and Ibrahim; adjusted regression-chain ratio quartile1,3 (AR-CRQ1,3) imputation of Kadilar and Cinji; adjusted regression-multivariate ratio quatile1,3 (AR-MRQ1,3) imputation of Feng, Ni, and Zou; and adjusted regression-multivariate chain ratio quartile1,3 (AR-MCRQ1,3) imputation of Lu for each simple random sampling (SRS) and rank set sampling (RSS). …”
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    Integration of multiple coinflip devices for high-quality random sampling by Brady Taylor, J. Darby Smith, Shashank Misra, James B. Aimone, Christopher R. Allemang

    Published 2025-07-01
    “…Abstract Artificial intelligence, scientific computing, and probabilistic computing use random sampling to approximate solutions to various problems, with larger models requiring a substantial quantity of random numbers. …”
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    Enhanced estimation of population mean using simple random sampling by Anoop Kumar, Asra Sayyed Siddiqui

    Published 2024-12-01
    “…The present study suggests an enhanced class of estimators for the population mean estimation utilizing simple random sampling (SRS). The bias, mean square errors (MSE), and minimum MSE of the suggested estimators are computed to the approximation of order one. …”
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    Sample Size Determination for the Polychotomous Randomized Response Model for Sensitive Questions in a Stratified Two-Stage Sampling Survey by Zongda Jin, Bo Yu, Xiangke Pu, Ge Gao

    Published 2014-01-01
    “…Methods of finding the minimum value and the Lagrange function were applied to deduce the formulae for the optimum sample sizes for polychotomous randomized response technique (RRT) model in stratified two-stage sampling, so as to minimize the cost for specified sampling errors and to minimize the sampling errors under the constraint of a fixed budget. …”
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    Statistical inference for the generalized exponential distribution using ordered lower k-record ranked set sampling with random sample sizes by Haidy A. Newer

    Published 2025-05-01
    “…By incorporating k-record values with random sample sizes, we develop maximum likelihood estimation, classical Bayes estimation, and empirical Bayes estimators, leveraging informative priors under balanced loss functions, including balanced squared error and balanced linear exponential. …”
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    Simulation-Based Inference: Random Sampling vs. Random Assignment? What Instructors Should Know by Beth Chance, Karen McGaughey, Sophia Chung, Alex Goodman, Soma Roy, Nathan Tintle

    Published 2025-01-01
    “…In particular, does it matter whether the simulation models random sampling or random assignment? We present examples from comparing two means and simple linear regression, highlighting the impact on the standard deviation of the null distribution. …”
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