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 ...
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 ...
Background We investigated the prevalence, temporal trends and associated factors of overweight and obesity among adults in ...
Abstract: Variable Subset Forecasting (VSF) presents a critical challenge where variable availability fluctuates between the training and inference stages. This paper introduces a novel solution to ...
Abstract: This study proposes a multivariate dynamic cost standard prediction model based on random forest; LSTM is combined with XGBoost to solve the problem of accuracy in predicting complex cost ...
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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