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为多元一般线性形式生成特征可控的测试数据AI 解读

Experiments to assess the performance characteristics, both of statistical methods and of computer programs that implement them, are best performed using test data with controlled statistical and numerical properties. We describe an algorithm for constructing test data for any multivariate linear model that provides complete control (subject only to the requirement of mutual consistency) over the following factors: regression coefficients; regression and residual sums of…

为多元一般线性模型生成特征可独立控制的测试数据AI 解读

Experiments to assess the performance characteristics, both of statistical methods and of computer programs that implement them, are best performed using test data with controlled statistical and numerical properties. We describe an algorithm for constructing test data for any multivariate linear model that provides complete control (subject only to the requirement of mutual consistency) over the following factors: regression coefficients; regression and residual sums of…

构造具有可控特征的回归：探查回归表现的方法AI 解读

Studies of robust regression algorithms have generally relied on Monte Carlo trials and have concentrated on evaluating the algorithm's performance for long-tailed error distributions. This article identifies other aspects of data structure that can influence the performance of robust regression procedures and presents an algorithm for constructing regression problems in which each of these factors can be controlled separately. The method generalizes to multiple regression…

构造具有可控特征的回归问题：考察回归性能的方法AI 解读

Studies of robust regression algorithms have generally relied on Monte Carlo trials and have concentrated on evaluating the algorithm's performance for long-tailed error distributions. This article identifies other aspects of data structure that can influence the performance of robust regression procedures and presents an algorithm for constructing regression problems in which each of these factors can be controlled separately. The method generalizes to multiple regression…