The minimum bias classification ratemaking proce-dure, introduced by Robert Bailey and LeRoy Simon in 1960, determines rate relativities simultaneously for two or more classification dimensions. This paper summa-rizes the minimum bias procedure for the practicing ac-tuary and provides the intuition for several bias func-tions: balance principle, least squares, Â-squared, and maximum likelihood. The exposition is structured around a series of illustrations using a two-dimensional private passenger automobile classification system: male/female and urban/rural
With the development of AI technology, more and more decisions are made by algorithms instead of hum...
International audienceApplications based on machine learning models have now become an indispensable...
Examines the effectiveness of a mean rating strategy, in which correlations are derived from ratings...
The paper “Insurance Rates with Minimum Bias ” by Robert A. Bailey [3] presents a methodology which ...
The apparent error rate is a commonly used estimator of the actual error rate in discrimi-nant analy...
International audienceStatistical algorithms are usually helping in making decisions in many aspects...
This paper presents a supplementary, valuable property of the minimum bias estimation (MBE) procedur...
In the present work we will study methods, which are used to find a premium in nonlife insurance acc...
We propose an assessor reallocation algorithm that aims to objectively reduce the marking biases of ...
Many problems in biomedical and other sciences are subject to biased estimates (maximum likelihood o...
The Minimal Detectable Bias (MDB) is an important diagnostic tool in data quality control. The MDB i...
Footnote: The middle red line represents the average bias Line. The bias is computed as the value de...
Ph.D.StatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.l...
One of the most important steps in formulating and solving a multiattribute decision-making (MADM) p...
Applications based on machine learning models have now become an indispensable part of the everyday ...
With the development of AI technology, more and more decisions are made by algorithms instead of hum...
International audienceApplications based on machine learning models have now become an indispensable...
Examines the effectiveness of a mean rating strategy, in which correlations are derived from ratings...
The paper “Insurance Rates with Minimum Bias ” by Robert A. Bailey [3] presents a methodology which ...
The apparent error rate is a commonly used estimator of the actual error rate in discrimi-nant analy...
International audienceStatistical algorithms are usually helping in making decisions in many aspects...
This paper presents a supplementary, valuable property of the minimum bias estimation (MBE) procedur...
In the present work we will study methods, which are used to find a premium in nonlife insurance acc...
We propose an assessor reallocation algorithm that aims to objectively reduce the marking biases of ...
Many problems in biomedical and other sciences are subject to biased estimates (maximum likelihood o...
The Minimal Detectable Bias (MDB) is an important diagnostic tool in data quality control. The MDB i...
Footnote: The middle red line represents the average bias Line. The bias is computed as the value de...
Ph.D.StatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.l...
One of the most important steps in formulating and solving a multiattribute decision-making (MADM) p...
Applications based on machine learning models have now become an indispensable part of the everyday ...
With the development of AI technology, more and more decisions are made by algorithms instead of hum...
International audienceApplications based on machine learning models have now become an indispensable...
Examines the effectiveness of a mean rating strategy, in which correlations are derived from ratings...