• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国政府科技报告 >Maximum-likelihood fitting of data dominated by Poisson statistical uncertainties
【24h】

Maximum-likelihood fitting of data dominated by Poisson statistical uncertainties

机译：由泊松统计不确定性支配的数据的最大似然拟合

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The fitting of data by (chi)(sup 2)-minimization is valid only when the uncertainties in the data are normally distributed. When analyzing spectroscopic or particle counting data at very low signal level (e.g., a Thomson scattering diagnostic), the uncertainties are distributed with a Poisson distribution. The authors have developed a maximum-likelihood method for fitting data that correctly treats the Poisson statistical character of the uncertainties. This method maximizes the total probability that the observed data are drawn from the assumed fit function using the Poisson probability function to determine the probability for each data point. The algorithm also returns uncertainty estimates for the fit parameters. They compare this method with a (chi)(sup 2)-minimization routine applied to both simulated and real data. Differences in the returned fits are greater at low signal level (less than (approximately)20 counts per measurement). the maximum-likelihood method is found to be more accurate and robust, returning a narrower distribution of values for the fit parameters with fewer outliers.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号