Tang, Lu Zhou, Ling Song, Peter X. K.
Published in
Computational Statistics

We propose a fusion learning procedure to perform regression coefficients clustering in the Cox proportional hazards model when parameters are partially heterogeneous across certain predefined subgroups, such as age groups. One major issue pertains to the fact that the same covariate may have different influence on the survival time across differen...

Song, Jiyeon Shin, Seung Jun
Published in
Computational Statistics

Principal component analysis (PCA) is a canonical tool that reduces data dimensionality by finding linear transformations that project the data into a lower dimensional subspace while preserving the variability of the data. Selecting the number of principal components (PC) is essential but challenging for PCA since it represents an unsupervised lea...

Melnykov, Volodymyr Zhu, Xuwen
Published in
Computational Statistics

Grouping similar objects into common groups, also known as clustering, is an important problem of unsupervised machine learning. Various clustering algorithms have been proposed in literature. In recent years, the need to analyze large amounts of data has led to reconsidering some fundamental clustering procedures. One of them is the celebrated K-m...

Kestler, Hans A. Bischl, Bernd Schmid, Matthias
Published in
Computational Statistics

Saboor, Abdus Khan, Muhammad Nauman Cordeiro, Gauss M. Pascoa, Marcelino A. R. Bortolini, Juliano Mubeen, Shahid
Published in
Computational Statistics

We introduce a flexible modified beta modified-Weibull model, which can accommodate both monotonic and non-monotonic hazard rates such as a useful long bathtub shaped hazard rate in the middle. Several distributions can be obtained as special cases of the new model. We demonstrate that the new density function is a linear combination of modified-We...

Bongiorno, Enea G. Goia, Aldo Vieu, Philippe
Published in
Computational Statistics

The paper deals with a test procedure able to state the compatibility of observed data with a reference model, by using an estimate of the volumetric part in the small-ball probability factorization which plays the role of a real complexity index. As a preliminary by-product we state some asymptotics for a new estimator of the complexity index. A s...

Baringhaus, L. Gaigall, D. Thiele, J. P.
Published in
Computational Statistics

The paper deals with the asymptotic behaviour of estimators, statistical tests and confidence intervals for L2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L^2$$\end{...

Sottile, Gianluca Adelfio, Giada
Published in
Computational Statistics

In this paper, we propose a new method for finding similarity of effects based on quantile regression models. Clustering of effects curves (CEC) techniques are applied to quantile regression coefficients, which are one-to-one functions of the order of the quantile. We adopt the quantile regression coefficients modeling (QRCM) framework to describe ...

Usami, Satoshi Jacobucci, Ross Hayes, Timothy
Published in
Computational Statistics

Behavioral researchers have shown growing interest in structural equation model trees (SEM Trees), a new recursive partitioning-based technique for detecting population heterogeneity. In the present research, we conducted a large-scale simulation to investigate the performance of latent growth curve model (LGCM)-based SEM Trees for uncovering betwe...

Massing, Till
Published in
Computational Statistics

Lévy processes have become very popular in many applications in finance, physics and beyond. The Student–Lévy process is one interesting special case where increments are heavy-tailed and, for 1-increments, Student t distributed. Although theoretically available, there is a lack of path simulation techniques in the literature due to its complicated...