{"title":"Fitting an Exponential Distribution","authors":"R. Fraile, E. García‐Ortega","doi":"10.1175/JAM2271.1","DOIUrl":null,"url":null,"abstract":"Abstract Exponential distributions of the type N = N0 exp(−λt) occur with a high frequency in a wide range of scientific disciplines. This paper argues against a widely spread method for calculating the λ parameter in this distribution. When the ln function is applied to both members, the equation of a straight line in t is obtained, which may be fit by means of linear regression. However, the paper illustrates that this is equivalent to a least squares fit with a weight function that assigns more importance to the higher values of t. It is argued that the method of maximum likelihood should be applied, because it takes into account all of the data equally. An iterative method for determining λ is proposed, based on the method of moments for cases in which only a truncated distribution is available.","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"2 1","pages":"1620-1625"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Meteorology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1175/JAM2271.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25
Abstract
Abstract Exponential distributions of the type N = N0 exp(−λt) occur with a high frequency in a wide range of scientific disciplines. This paper argues against a widely spread method for calculating the λ parameter in this distribution. When the ln function is applied to both members, the equation of a straight line in t is obtained, which may be fit by means of linear regression. However, the paper illustrates that this is equivalent to a least squares fit with a weight function that assigns more importance to the higher values of t. It is argued that the method of maximum likelihood should be applied, because it takes into account all of the data equally. An iterative method for determining λ is proposed, based on the method of moments for cases in which only a truncated distribution is available.
N = N0 exp(−λt)型指数分布在许多科学学科中出现的频率很高。本文反对在这种分布中计算λ参数的一种广为流传的方法。当ln函数作用于两个成员时,得到t中的直线方程,可以用线性回归的方法拟合。然而,本文说明,这相当于最小二乘拟合与权重函数,赋予更大的重要性的t值。有人认为,最大似然的方法应该应用,因为它平等地考虑所有的数据。对于截断分布的情况,提出了一种基于矩量法的迭代求解λ的方法。