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 ...
Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn ...
TSD 20: Multivariate meta-analysis of summary data for combining treatment effects on correlated outcomes and evaluating surrogate endpoints (PDF, 1.2MB) – October 2019 – Updated December 2022: ...
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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