Description

In this episode, I found that Bambi (Bayesian Model Building Interface) is more than a little deer, rooted for the round-robin operator for genetic algorithms, and had my convictions that machine learning is not magic reinforced.

References:

• HighFrequencyCovariance:  A Julia Package for Estimating Covariance Matrices Using High Frequency Financial Data
• Bambi: A Simple Interface for Fitting Bayesian Linear Models in Python
• Spbsampling: An R Package for Spatially Balanced Sampling
• plot3logit: Ternary Plots for Interpreting Trinomial Regression Models
• Learning Base R (2nd Edition)
• Python and R for the Modern Data Scientist
• Genetic algorithm with a new round-robin based tournament selection: Statistical properties analysis
• Healthcare researchers must be wary of misusing AI
• New method to identify symmetries in data using Bayesian statistics
• Python 3.11.0rc2 is now available
• Complex Layouts using the SG Procedures
• Factor Analysis Guide with an Example
• How to Choose Appropriate Clustering Method for Your Dataset
• How to Apply AI to Small Data Sets?
• The R Consortium Needs Your Help with satRdays
• Visualizing OLS Linear Regression Assumptions in R

R-packages:

• TPCselect:  Variable Selection via Threshold Partial Correlation
• historicalborrow:  Non-Longitudinal Bayesian Historical Borrowing Models
• historicalborrowlong:  Longitudinal Bayesian Historical Borrowing Models
• kgp:  1000 Genomes Project Metadata
• DBIsqldf:  Manipulate R Data Frames Using SQL
• latentFactoR:  Data Simulation Based on Latent Factors
• TSdeeplearning:  Deep Learning Model for Time Series Forecasting