最大化
缩小
期望最大化算法
数学
统计
限制
蒙特卡罗方法
应用数学
最小二乘函数近似
算法
标准误差
计算机科学
最大似然
数学优化
估计员
工程类
机械工程
出处
期刊:Journal of Immunology
[American Association of Immunologists]
日期:1981-04-01
卷期号:126 (4): 1614-1619
被引量:1249
标识
DOI:10.4049/jimmunol.126.4.1614
摘要
Abstract A statistical method was developed for the analysis of experimental data from limiting dilution assays. Formulas for the estimation of the frequency of immunocompetent cells within a test population were derived by the statistical methods of weighted averaging, likelihood maximization, and X2 minimization. Equations for the latter 2 were solved by Newton's method of iterative approximation. Estimates obtained by these methods were found to be more valid than those obtained by least squares (LS) fitting as judged by the X2 test and as established by Monte Carlo experiments. X2 minimization was chosen as the preferable estimation method with maximum accuracy and precision (minimum bias and variance) for the standard determination of frequencies; likelihood maximization was used only for the confirmation of results. When data from previously published experiments were reanalyzed, both results and conclusions were found to differ significantly from those originally obtained by LS fitting, thus demonstrating the importance of using proper data analysis methods. In conjunction with the use of available calculators or microcomputers, the method presented here provides a simple and rapid procedure for the valid determination of immunocompetent cell frequencies.
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