{"title":"截断帕累托分布与损失分布的拟合","authors":"A. V. Boyd","doi":"10.1017/S2049929900010291","DOIUrl":null,"url":null,"abstract":"Hogg and Klugman use the truncated Pareto distribution with probability density function where δ ≥0 is specified and α > 0 and λ > 0 are unknown parameters, to describe insurance claims. This is fitted first of all by the method of moments, using the estimators and where is the mean of a simple random sample, and the (biased) variance The authors then suggest, on pp. 113–16, that these estimates be used as starting values in a Newton iteration to get the maximum likelihood estimates of the parameters, but this technique can fail as a result of convergence problems. The object of this note is to show that this has led Hogg and Klugman to underestimate seriously the area in the tail of a fitted loss distribution, and to discuss a method of circumventing this difficulty.","PeriodicalId":419781,"journal":{"name":"Journal of the Staple Inn Actuarial Society","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Fitting the Truncated Pareto Distribution to Loss Distributions\",\"authors\":\"A. V. Boyd\",\"doi\":\"10.1017/S2049929900010291\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hogg and Klugman use the truncated Pareto distribution with probability density function where δ ≥0 is specified and α > 0 and λ > 0 are unknown parameters, to describe insurance claims. This is fitted first of all by the method of moments, using the estimators and where is the mean of a simple random sample, and the (biased) variance The authors then suggest, on pp. 113–16, that these estimates be used as starting values in a Newton iteration to get the maximum likelihood estimates of the parameters, but this technique can fail as a result of convergence problems. The object of this note is to show that this has led Hogg and Klugman to underestimate seriously the area in the tail of a fitted loss distribution, and to discuss a method of circumventing this difficulty.\",\"PeriodicalId\":419781,\"journal\":{\"name\":\"Journal of the Staple Inn Actuarial Society\",\"volume\":\"83 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1988-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Staple Inn Actuarial Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1017/S2049929900010291\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Staple Inn Actuarial Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/S2049929900010291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fitting the Truncated Pareto Distribution to Loss Distributions
Hogg and Klugman use the truncated Pareto distribution with probability density function where δ ≥0 is specified and α > 0 and λ > 0 are unknown parameters, to describe insurance claims. This is fitted first of all by the method of moments, using the estimators and where is the mean of a simple random sample, and the (biased) variance The authors then suggest, on pp. 113–16, that these estimates be used as starting values in a Newton iteration to get the maximum likelihood estimates of the parameters, but this technique can fail as a result of convergence problems. The object of this note is to show that this has led Hogg and Klugman to underestimate seriously the area in the tail of a fitted loss distribution, and to discuss a method of circumventing this difficulty.