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How to run R-style linear regressions in Python the easy way

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can ...
Scientific Research Publishing

West, B.T., Welch, K.B. and Galecki, A.T. (2015) Linear Mixed Models: A Practical Guide Using Statistical Software. 2nd Edition, CRC Press.

ABSTRACT: This research evaluates the effect of monetary policy rate and exchange rate on inflation across continents using both Frequentist and Bayesian Generalized Additive Mixed Models (GAMMs).
Scientific Research Publishing

Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B., Vehtari, A. and Rubin, D.B. (2013) Bayesian Data Analysis. 3rd Edition, CRC Press.

ABSTRACT: This research evaluates the effect of monetary policy rate and exchange rate on inflation across continents using both Frequentist and Bayesian Generalized Additive Mixed Models (GAMMs).
GitHub

[ENH] Expand simulation capability of Linear Gaussian Bayesian Networks

The LinearGaussianBayesianNetwork.simulate method currently provides some basic functionality to generate data from the model. Compared to DiscreteBayesianNetwork, this function is quite limiting as ...
IEEE

An Ensemble Bayesian Dynamic Linear Model for Human Activity Recognition

Abstract: Human activity recognition (HAR) has been gaining attention in recent years as a result of its many applications in health, sports, entertainment, and surveillance. Due to the current ...
Frontiers

Bayesian regression modeling and inference of energy efficiency data: the effect of collinearity and sensitivity analysis

The majority of research predicted heating demand using linear regression models, but they did not give current building features enough context. Model problems such as Multicollinearity need to be ...
ascopubs.org

Associations Between Radiation Oncologist Demographic Factors and Segmentation Similarity Benchmarks: Insights From a Crowd-Sourced Challenge Using Bayesian Estimation

The quality of radiotherapy auto-segmentation training data, primarily derived from clinician observers, is of utmost importance. However, the factors influencing the quality of clinician-derived ...
IEEE

Bayesian Inference for Non-Linear Forward Model by Using a VAE-Based Neural Network Structure

Abstract: In this paper, a Variational Autoencoder (VAE) based framework is introduced to solve parameter estimation problems for non-linear forward models. In particular, we focus on applications in ...