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 ...
Intrinsic neural attractors and extrinsic environmental inputs jointly steer the dynamic trajectories of brain activity ...
Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...
Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn to assess risk and potential gains.
Abstract: Extended dispersion entropy-based Lempel–Ziv complexity (EDELZC) can measure the irregularity or chaos of single-channel time series, which is one of the ideal tools for extracting fault ...
Background To evaluate the efficacy and safety of repeated low-level red-light (RLRL) therapy for controlling myopia ...
Abstract: Multivariate Time Series (MTS) forecasting is crucial in many domains, such as financial market analysis, weather forecasting and energy management. Among various solutions for this task, ...
Model-based clustering provides a principled way of developing clustering methods. We develop a new model-based clustering methods for count data. The method combines clustering and variable selection ...
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