Search
Search Results
-
Multi-feature clustering of step data using multivariate functional principal component analysis
This study presents a new statistical method for clustering step data, a popular form of health recording data easily obtained from wearable devices....
-
Multivariate Leimkuhler Curve: Properties and Applications to Analysis of Bibliometric Data
The Leimkuhler curve has established itself as an efficient tool in the analysis and comparison of concentration of bibliometric measures of...
-
Bayesian Analysis of Multivariate Matched Proportions with Sparse Response
Multivariate matched proportions (MMP) data appear in a variety of contexts including post-market surveillance of adverse events in pharmaceuticals,...
-
Constrained Multivariate Functional Principal Components Analysis for Novel Outcomes in Eye-Tracking Experiments
Individuals with autism spectrum disorder (ASD) tend to experience greater difficulties with social communication and sensory information processing....
-
A Random-Coefficients Analysis with a Multivariate Random-Coefficients Linear Model
Random-coefficients linear models can be considered as a particular case of linear mixed models. Different sources of variation are treated by random...
-
Multivariate Statistical Process Control
As was discussed in Chap. 4 in Modern Statistics (Kenett et al. (Modern statistics: a computer-based...
-
Multivariate Hawkes processes with spatial covariates for spatiotemporal event data analysis
Spatiotemporal events occur in many disciplines, including economics, sociology, criminology, and seismology, with different patterns in space and...
-
Multivariate functional subspace classification for high-dimensional longitudinal data
We propose a multi-class classification method for multivariate functional data using the subspace method. The subspace method reduces the dimension...
-
Multivariate Functional Singular Spectrum Analysis: A Nonparametric Approach for Analyzing Multivariate Functional Time Series
In this chapter, we develop multivariate functional singular spectrum analysis (MFSSA) over different dimensional domains with the goal of...
-
Bayesian Multivariate Analysis of Mixed Data
Graphical models provide an effective tool to represent conditional independences among variables. While this class of models has been extensively...
-
Multivariate Doubly Truncated Moments for a Class of Multivariate Location-Scale Mixture of Elliptical Distributions
AbstractIn this paper, we investigate multivariate doubly truncated moments for a class of multivariate location-scale mixture of elliptical (LSME)...
-
On Computing the Multivariate Poisson Probability Distribution
Within the theory of non-negative integer valued multivariate infinitely divisible distributions, the multivariate Poisson distribution plays a key...
-
Regression-type analysis for multivariate extreme values
This paper devises a regression-type model for the situation where both the response and covariates are extreme. The proposed approach is designed...
-
Multivariate Varying Coefficient Spatiotemporal Model
As of 2020, 807,920 individuals in the U.S. had end-stage kidney disease (ESKD) with about 70% of patients on dialysis, a life-sustaining treatment....
-
Topological Data Analysis for Directed Dependence Networks of Multivariate Time Series Data
Topological data analysis (TDA) approaches are becoming increasingly popular for studying the dependence patterns in multivariate time series data....
-
Multivariate Hidden Markov Models
This chapter provides three extended example analyses, applying hidden Markov models to multivariate time series. The first example (Sect. 6.1)...
-
Multivariate Linear Regression
Regression methods are perhaps the most widely used statistical tools in data analysis. When several response variables are studied simultaneously,...
-
Addressing non-normality in multivariate analysis using the t-distribution
The main aim of this paper is to propose a set of tools for assessing non-normality taking into consideration the class of multivariate t -distribution...
-
Regression Trees and Ensemble for Multivariate Outcomes
Tree-based methods have become one of the most flexible, intuitive, and powerful analytic tools for exploring complex data structures. The best...
-
A distance based two-sample test of means difference for multivariate datasets
In the paper we present a new test for comparison of the means of multivariate samples with unknown distributions. The test is based on the...
