Provides nonparametric Steinian shrinkage estimators of the covariance matrix that are suitable in high dimensional settings, that is when the number of variables is larger than the sample size.

Efficient Markov chain Monte Carlo (MCMC) algorithms for fully 
    Bayesian estimation of dynamic survival models with shrinkage priors. 
    Details on the algorithms used are provided in Wagner (2011) <doi:10.1007/s11222-009-9164-5>, 
    Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006> and
    Cadonna et al. (2020) <doi:10.3390/econometrics8020020>.

Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models with shrinkage priors, both dynamic and static. Details on the algorithms used are provided in Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006> and  
  Cadonna et al. (2020) <doi:10.3390/econometrics8020020> and Knaus and Frühwirth-Schnatter (2023)  <doi:10.48550/arXiv.2312.10487>. For details on the package, please see Knaus et al. (2021) <doi:10.18637/jss.v100.i13>.

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.