Description

In this episode I thought outside the Box-Pierce; fuzzed, sweated, and flustered my way through basic stats; encountered functions and AI for babies; and chronicled the R-package ‘chronicler’.

References:

• NeuralSens: Sensitivity Analysis of Neural Networks
• econet: An R Package for Parameter-Dependent Network Centrality Measures
• Modified Quantile Regression For Modeling the Low Birth Rate
• A Novel Correction for the Adjusted Box-Pierce Test
• Comments on identifying causal relationships in nonlinear dynamical systems via empirical mode decomposition
• Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing
• The balanced bootstrap in SAS
• Game-changer AI tool will save mothers and babies
• D. Mayo & D. Hand: “Statistical significance and its critics: practicing damaging science, or damaging scientific practice?”
• Fuzzy Clustering: Definition
• How to Find the P value: Process and Calculations
• The Difference Between an Odds Ratio and a Predicted Odds
• ‘Data analysis with tidyverse’ workshop
• Think like a programmeR: the workshop
• How to add labels at the end of each line in ggplot2?
• Subsetting with multiple conditions in R
• Hierarchical data visualization with Shiny and D3
• chronicler: Add Logging to Functions

R-packages:

• Rwclust: Random Walk Clustering on Weighted Graphs
• ScaleSpikeSlab: Scalable Spike-and-Slab
• webshot2: Take Screenshots of Web Pages
• mverse: Tidy Multiverse Analysis Made Simple
• chronicler: Adding Logging to Functions