Showing 61 - 80 results of 8,228 for search 'Linear sampling', query time: 0.13s Refine Results
  1. 61

    Estimation of Log-Linear-Binomial Distribution with Applications by Elsayed Ali Habib

    Published 2010-01-01
    “…Log-linear-binomial distribution was introduced for describing the behavior of the sum of dependent Bernoulli random variables. …”
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  2. 62

    Fiducial Inference in Linear Mixed-Effects Models by Jie Yang, Xinmin Li, Hongwei Gao, Chenchen Zou

    Published 2025-02-01
    “…We develop a novel framework for fiducial inference in linear mixed-effects (LME) models, with the standard deviation of random effects reformulated as coefficients. …”
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    Article
  3. 63
  4. 64

    Learning from low precision samples by Ji In Choi, Madeleine Georges, Jung Ah Shin, Olivia Wang, Tiffany Zhu, Tapan Shah

    Published 2021-04-01
    “…In dithering, additive noise from a uniform distribution is added to the sample before quantization. In stochastic rounding, each sample is quantized to the upper level with probability p and to a lower level with probability 1-p. …”
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  5. 65

    Comprehensive measurement of purines in biological samples by Rong Fu, Diane J. Sutcliffe, Ashok R. Dinasarapu, Ellen J. Hess, Ellen J. Hess, H. A. Jinnah, H. A. Jinnah

    Published 2025-07-01
    “…Samples from cultured human cells were prepared to assess the applicability of the method in biological samples. …”
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    Article
  6. 66
  7. 67

    Non-Linear Super-Stencils for turbulence model corrections by Jonas Luther, Patrick Jenny

    Published 2025-06-01
    “…Here, we introduce the Non-Linear Super-Stencil (NLSS), that is, a compact stencil sampling local mean flow features and mapping them to a corrective force term by employing a neural network. …”
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    Article
  8. 68

    The Albedo of Pervious Cement Concrete Linearly Decreases with Porosity by Rui Zhang, Guosheng Jiang, Jia Liang

    Published 2015-01-01
    “…Four Portland cement concrete mixes were casted, using designed amounts of sand to vary the porosity of the pervious concrete samples. The samples were sliced and the spectral reflectance and albedo of the sliced samples were measured and analyzed. …”
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  9. 69

    Application of the Fuzzy Classification for Linear Hybrid Prediction Methods by A. S. Taskin, E. M. Mirkes, N. Y. Sirotinina

    Published 2013-06-01
    “…The paper discusses the problem of forecasting for samples with real-valued attributes. The goal is to estimate the effect of generated binary attributes on forecasting accuracy for the linear regression and the hybrid methods based on clustering. …”
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    Article
  10. 70

    Enhanced superconductivity at a corner for the linear BCS equation by Barbara Roos, Robert Seiringer

    Published 2025-01-01
    “…We consider the critical temperature for superconductivity, defined via the linear BCS equation. We prove that at weak coupling the critical temperature for a sample confined to a quadrant in two dimensions is strictly larger than the one for a half-space, which in turn is strictly larger than the one for $\mathbb {R}^2$ . …”
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  11. 71

    Genetic Linear Averaging Algorithm for Zooming Digital Images by Baydaa Bahnam

    Published 2013-07-01
    “…In this paper, the hypernation of linear averaging algorithm for zooming images is achieved with genetic algorithm. …”
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    Article
  12. 72

    Linear low density polyethylene/cycloolefin copolymer blends

    Published 2011-01-01
    “…Linear low density polyethylene (LLDPE) was melt compounded with various amounts of a cycloolefin copolymer (COC). …”
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    Article
  13. 73

    Classifying Raman Spectra of Colon Cells by Principal Component Analysis—Linear Discriminant Analysis and Partial Least Squares—Linear Discriminant Analysis Methods by Maria Lasalvia, Vito Capozzi, Giuseppe Perna

    Published 2025-04-01
    “…Linear discriminant analysis of a few principal components and partial least squares components was used to estimate the classification accuracy of a set of Raman spectra measured inside nucleus and cytoplasm. …”
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  14. 74
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  16. 76

    Comparison of Matrix Decomposition in Null Space-Based LDA Method by Carissa Devina Usman, Farikhin, Titi Udjiani

    Published 2024-06-01
    Subjects: “…linear discriminant analysis…”
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    Article
  17. 77

    HPTLC assay of nicotine and cotinine in biological samples by Ana Maria Vlasceanu, Daniela Luiza Baconi, Anne Marie Ciobanu, Vlad D. Constantin, Liana Pleș, Cristian Balalau, Miriana Stan

    Published 2018-10-01
    “…The regression curves were linear (with a corresponding correlation coefficient higher than 0.99) in the quantities range of 200 ng–1000 ng/spot for both nicotine and cotinine. …”
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  18. 78

    SOME SAMPLE TEST RESULTS FOR ABRASIVE WEAR by Valeri A. Petrovsky, Anatoliy R. Ruban, Ali Salamekh

    Published 2018-03-01
    “…The dependences of the mass Δm and the linear Δl abrasions, as well as the relative wear resistance Im, Il on the hardness, are plotted. …”
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  19. 79

    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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  20. 80

    Exploiting collider bias to apply two-sample summary data Mendelian randomization methods to one-sample individual level data. by Ciarrah Barry, Junxi Liu, Rebecca Richmond, Martin K Rutter, Deborah A Lawlor, Frank Dudbridge, Jack Bowden

    Published 2021-08-01
    “…With the advent of large and accessible fully-genotyped cohorts such as UK Biobank, there is now increasing interest in understanding how best to apply these well developed summary data methods to individual level data, and to explore the use of more sophisticated causal methods allowing for non-linearity and effect modification. In this paper we describe a general procedure for optimally applying any two sample summary data method using one sample data. …”
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