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关于非中心χ~2分布性质的研究 被引量:2
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作者 张绍璞 《天津科技大学学报》 CAS 2009年第1期75-78,共4页
χ2分布是多元分析中重要的分布之一,在参数估计、假设检验、回归分析和判别分析等领域中有广泛的应用.旨在证明非中心χ2分布的几个重要性质和结论,重点讨论经线性变换后的n维正态随机向量的二次型所构成的分布,给出其非中心参数的具... χ2分布是多元分析中重要的分布之一,在参数估计、假设检验、回归分析和判别分析等领域中有广泛的应用.旨在证明非中心χ2分布的几个重要性质和结论,重点讨论经线性变换后的n维正态随机向量的二次型所构成的分布,给出其非中心参数的具体计算公式.简化变换后非中心χ2分布的计算,并说明了这些结论在多元分析中的作用. 展开更多
关键词 多元分析 协方差矩阵 非中心χ2分布 参数 逆矩阵
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Comparison between global phenomenological and microscopic optical potentials for proton as projectile below 100 MeV 被引量:2
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作者 李小华 梁春恬 蔡崇海 《Chinese Physics C》 SCIE CAS CSCD 2009年第6期415-422,共8页
For 112 target nuclei (52 elements) with proton as projectile, we calculate the reaction cross sections and elastic scattering angular distributions, as well as the X^2 values for 16 kinds of proton optical model po... For 112 target nuclei (52 elements) with proton as projectile, we calculate the reaction cross sections and elastic scattering angular distributions, as well as the X^2 values for 16 kinds of proton optical model potentials: two sets of phenomenological global optical potentials and the microscopic optical potentials proposed by Shen et al for 14 sets of Skyrme force parameters: GSI-6, SBJS, SKM, SGI-Ⅱ, SKa-b, SCOI-Ⅱ. We find that for obtaining the proton microscopic optical potential based on the nuclear matter approach with Skyrme force, SGI, SKa and SKb are the three sets of optimal Skyrme force parameters. 展开更多
关键词 microscopic optical potential Skyrme force parameter elastic scattering angular distributions reaction cross sections X^2 value
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Estimating geographic variation of infection fatality ratios during epidemics
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作者 Joshua Ladau Eoin L.Brodie +12 位作者 Nicola Falco Ishan Bansal Elijah B.Hoffman Marcin P.Joachimiak Ana M.Mora Angelica M.Walker Haruko M.Wainwright Yulun Wu Mirko Pavicic Daniel Jacobson Matthias Hess James B.Brown Katrina Abuabara 《Infectious Disease Modelling》 2024年第2期634-643,共10页
Objectives We aim to estimate geographic variability in total numbers of infections and infection fatality ratios(IFR;the number of deaths caused by an infection per 1,000 infected people)when the availability and qua... Objectives We aim to estimate geographic variability in total numbers of infections and infection fatality ratios(IFR;the number of deaths caused by an infection per 1,000 infected people)when the availability and quality of data on disease burden are limited during an epidemic.Methods We develop a noncentral hypergeometric framework that accounts for differential probabilities of positive tests and reflects the fact that symptomatic people are more likely to seek testing.We demonstrate the robustness,accuracy,and precision of this framework,and apply it to the United States(U.S.)COVID-19 pandemic to estimate county-level SARS-CoV-2 IFRs.Results The estimators for the numbers of infections and IFRs showed high accuracy and precision;for instance,when applied to simulated validation data sets,across counties,Pearson correlation coefficients between estimator means and true values were 0.996 and 0.928,respectively,and they showed strong robustness to model misspecification.Applying the county-level estimators to the real,unsimulated COVID-19 data spanning April 1,2020 to September 30,2020 from across the U.S.,we found that IFRs varied from 0 to 44.69,with a standard deviation of 3.55 and a median of 2.14.Conclusions The proposed estimation framework can be used to identify geographic variation in IFRs across settings. 展开更多
关键词 Infection fatality ratio Infection fatality rate noncentral hypergeometric distribution COVID-19 SARS-CoV-2
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