A Full-Pipeline Automated Time Series (AutoTS) Analysis Toolkit.
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Updated
Jul 1, 2024 - Python
A Full-Pipeline Automated Time Series (AutoTS) Analysis Toolkit.
Conquering confounds and covariates: methods, library and guidance
NPDR: Nearest-neighbor Projected-Distance Regression with the generalized linear model
Shiny-Tool for investigation of metabolite-covariate relationships
IPW- and CBPS-type propensity score reweighting, with various extensions (Stata package)
Tutorials illustrating the use of baseline information to conduct more efficient randomized trials
SAMUEL-ROSA, A. et al. Do more detailed environmental covariates deliver more accurate soil maps? Geoderma, v. 243–244, p. 214–227, maio 2015.
Survival analysis of university completion. R(Survival Analysis), Python(EDA)
[IJHCS] UTA7: a clinical dataset with medical imaging and patient co-variables.
Project to practice time series forecasting (chiefly from Prof. Hyndman's book "Forecasting: Principles and Practice"). Forecasting hourly electricity consumption from the Duquesne Light Company around the Pittsburgh area.
R implementations of a variational EM approach for Stochastic Block Model with covariates
Covariate Software Failure and Reliability Assessment Tool (C-SFRAT). To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001588
Analyzing the spatial patterns of Canada Lynx locations and building a model to predict their location.
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