In this study, we propose a new measure for evaluating the predictive performance of regression models that considers their ADs. The purpose is not selecting the best regression model among various competing models, but determining an appropriate model group corresponding to the AD of each model. ...
Explained Variation and Predictive Accuracy in General Parametric Statistical Models: The Role of Model Misspecification When studying a regression model measures of explained variation are used to assess the degree to which the covariates determine the outcome of interest. M... Susanne Rosthj,N Keidi...
A measure of information contained in an estimating equation is defined using a result by Godambe (1960); this leads to the corresponding definition of efficiency of an estimating equation. The definitions are then extended to the multiparametric case. Also, results are established concerning the am...
Aim/Purpose The aim of this study was to analyze various performance metrics and approaches to their classification. The main goal of the study was to develop a new typology that will help to advance knowledge of metrics and facilitate their use in machine learning regression algorithms Background...
Lastly, in order to examine trait-like stability of a cognitive ability, measures must be repeated across days, as has been stressed in previous studies63,64,65,66,67,68. While some studies have tried to estimate transient change over days and model true trait-like performance69,70, it rem...
We investigate the empirical performance of default probability prediction based on Merton's (1974) structural credit risk model. More specifically, we stu... D Yu,W Suo - 中国金融国际年会 被引量: 28发表: 2007年 Large Unbalanced Credit Scoring Using Lasso-Logistic Regression Ensemble We show th...
To accurately evaluate the segmentation effect of this algorithm on the femoral regions, The Dice coefficient and Mean Intersection over Union (MIoU) index were used to evaluate the performance of the segmentation. Dice coefficient is a set similarity measurement function, which is usually used to ...
In this study, the Variance method will be used almost exclusively to model the relationship between the data from the two sites. Linear regression will be used when the applicability of using the uncertainties of the slope and offset for estimating the standard deviation of the results is being...
New assets may be ranked according to the magnitude of their performance contribution. The improvements in a portfolio are easily computable from the same linear regression employed to calculate an asset's Jensen measure. Thus, the appeal of the security market line as a useful financial tool may...
c, Estimated performance of predicted intensity model as correlation between actual and predicted intensity on k-fold test-set (Supplementary Methods). Expected variance estimated using cross-validation (k varied according to the number of molecules (n) used in each concentration; k = 8, 10, 10...