Model-based clustering using a new multivariate skew distribution

IF 1.4 4区计算机科学 Q2 STATISTICS & PROBABILITY

Advances in Data Analysis and Classification Pub Date : 2023-07-22 DOI:10.1007/s11634-023-00552-8

Salvatore D. Tomarchio, Luca Bagnato, Antonio Punzo

引用次数: 0

Abstract

Quite often real data exhibit non-normal features, such as asymmetry and heavy tails, and present a latent group structure. In this paper, we first propose the multivariate skew shifted exponential normal distribution that can account for these non-normal characteristics. Then, we use this distribution in a finite mixture modeling framework. An EM algorithm is illustrated for maximum-likelihood parameter estimation. We provide a simulation study that compares the fitting performance of our model with those of several alternative models. The comparison is also conducted on a real dataset concerning the log returns of four cryptocurrencies.

Abstract Image

查看原文本刊更多论文

使用新的多元倾斜分布进行基于模型的聚类

真实数据往往呈现出非正态分布的特征，如不对称和重尾，并呈现出潜在的群体结构。在本文中，我们首先提出了可以解释这些非正态分布特征的多元偏移指数正态分布。然后，我们在有限混合物建模框架中使用这种分布。说明了最大似然参数估计的 EM 算法。我们提供了一项模拟研究，比较了我们的模型与其他几个模型的拟合性能。比较还在一个有关四种加密货币对数收益的真实数据集上进行。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Advances in Data Analysis and Classification STATISTICS & PROBABILITY-

CiteScore

3.40

自引率

6.20%

发文量

审稿时长

>12 weeks

期刊介绍： The international journal Advances in Data Analysis and Classification (ADAC) is designed as a forum for high standard publications on research and applications concerning the extraction of knowable aspects from many types of data. It publishes articles on such topics as structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets; methods for the extraction of knowledge from data, and applications of advanced methods in specific domains of practice. Articles illustrate how new domain-specific knowledge can be made available from data by skillful use of data analysis methods. The journal also publishes survey papers that outline, and illuminate the basic ideas and techniques of special approaches.