Titlebook: Statistical Learning and Modeling in Data Analysis; Methods and Applicat Simona Balzano,Giovanni C. Porzio,Maurizio Vichi Conference procee

不自然

巩固

圆柱

LOPE

BYRE

Directional Supervised Learning Through Depth Functions: An Application to ECG Waves Analysis,vent sudden and untimely deaths. Here, directional depth-based classifiers are employed to predict the presence or absence of cardiac arrhythmia. A comparison of their performance with respect to the directional Bayes rule is also provided.

grandiose

Penalized Versus Constrained Approaches for Clusterwise Linear Regression Modeling,opose to solve the degeneracy problem by using a penalized approach: this is done by adding a penalty term to the log-likelihood function which increasingly penalizes smaller values of the scale parameters, and the tuning of the penalty term is done based on the data. Another traditional solution to

杀人

Effect Measures for Group Comparisons in a Two-Component Mixture Model: A Cyber Risk Analysis,form distribution is used to model indecision and the standard cumulative model is employed for the analysis of evaluation. We present probability-based measures for comparing clusters on ratings, while adjusting for other explanatory variables, and discuss marginal effects to address the interpreta

RADE

,A Cramér–von Mises Test of Uniformity on the Hypersphere,and not the magnitudes) are of interest. In this work, a projection-based Cramér–von Mises test of uniformity on the hypersphere is introduced. This test can be regarded as an extension of the well-known Watson test of circular uniformity to the hypersphere. The null asymptotic distribution of the t

adduction

finite

Robust Depth-Based Inference in Elliptical Models,ct to their halfspace depth and their illumination. The densities of elliptically symmetric distributions are expressed only in terms of the depth, the illumination, and a univariate function that can be estimated from the data. These observations set the ground for robust and nonparametric inferenc