Programmatic access to Flipside Crypto data via the Compass RPC API: <https://api-docs.flipsidecrypto.xyz/>. As simple as auto_paginate_query() but with core functions as needed for troubleshooting. Note, 0.1.1 support deprecated 2023-05-31.

We provide a collection of statistical hypothesis testing procedures ranging from classical to modern methods for non-trivial settings such as high-dimensional scenario. For the general treatment of statistical hypothesis testing, see the book by Lehmann and Romano (2005) <doi:10.1007/0-387-27605-X>.

Implementation of the shuffle estimator, a non-parametric estimator for signal and noise variance under mild noise correlations.

Scripts and exercises that use card shuffling to teach confidence interval comparisons for different estimators.

Shows the scatter plot along with the fitted regression lines. It 
  depicts min, max, the three quartiles, mean, and sd for each variable.
  It also depicts sd-line, sd-box, r, r-square, prediction boundaries, and regression outliers.

Package including additional modules for interactive
    'ShinyItemAnalysis' application for the psychometric analysis of
    educational tests, psychological assessments, health-related and other
    types of multi-item measurements, or ratings from multiple raters.

A comprehensive suite of functions designed for constructing
    and managing 'ShinyItemAnalysis' modules, supplemented with detailed
    guides, ready-to-use templates, linters, and tests. This package
    allows developers to seamlessly create and integrate one or more
    modules into their existing packages or to start a new module project
    from scratch.

Fits bi-variate ellipses to stable isotope data using Bayesian
    inference with the aim being to describe and compare their isotopic
    niche.

Provides models to identify bimodally expressed genes from
 RNAseq data based on the Bimodality Index. SIBERG models the  RNAseq data in
 the finite mixture modeling framework and incorporates mechanisms  for
 dealing with RNAseq normalization. Three types of mixture models are
 implemented,  namely, the mixture of log normal, negative binomial, or 
 generalized Poisson distribution. See Tong et al. (2013)
 <doi:10.1093/bioinformatics/bts713>.