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A comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, 2012). Implementations of various estimation methods suggested in the literature are included. Additional compelling features comprise posterior probabilities, an implementation of an expectation-maximization (EM) algorithm, and PIN decomposition into layers, and into bad/good components. Versatile data simulation tools, and trade classification algorithms are among the supplementary utilities. The package provides fast, compact, and precise utilities to tackle the sophisticated, error-prone, and time-consuming estimation procedure of informed trading, and this solely using the raw trade-level data.
A statistical test of pleiotropic effect of a genetic variant on two traits using GWAS summary statistics
PyTorch implementation of the mixture distribution family with implicit reparametrisation gradients.
An R package containing functions for clustering multivariate data using mixtures of factor analyzers.
Importance sampling with control variates on top of Distributions.jl
Raku package for statistical distributions and related random variates generations.
Provides the r,p,d,q functions for mixtures of standard R distributions