Halva—‘grapHical Analysis with Latent VAriables’—is a Python package dedicated to statistical analysis of multivariate ordinal data, designed specifically to handle missing values and latent variables ...
Analysis of Multivariate Indoor Building Data: A Comparative Study of Time-Series Clustering Methods
Abstract: Clustering multivariate time-series data is crucial for uncovering complex temporal patterns in dynamic environments, such as building indoor conditions and behavior where variables like ...
Abstract: The past decade has witnessed the success of deep learning-based multivariate time series forecasting in Internet of Things (IoT) systems. However, dynamic variable correlation remains a ...
Leveraging AI to help analyze and visualize data gathered from a variety of data sets enables data-driven insights and fast analysis without the high costs of talent and technology. In today's ...
Department of Economics, FEARP - Faculty of Economics, Business Administration and Accounting at Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil Introduction: Realized volatility ...
Permutational Multivariate Analysis of Variance (PERMANOVA) is a non-parametric statistical method used to assess the differences in multivariate data among groups or treatments. It is particularly ...
Multivariate analysis of variance (MANOVA) is a widely used technique for simultaneously comparing means for multiple dependent variables across two or more groups. MANOVA rests on several assumptions ...
ABSTRACT: In many applications, such as in multivariate meta-analysis or in the construction of multivariate models from summary statistics, the covariance of regression coefficients needs to be ...
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