Suggests: knitr, rmarkdown, survival, markdown

Description: Provides a robust approach for omics data integration and disease subtyping. PINSPlus is fast and supports the analysis of large datasets with hundreds of thousands of samples and features. The software automatically determines the optimal number of clusters and then partitions the samples in a way such that the results are robust against noise and data perturbation (Nguyen et al. (2019) <DOI: 10.1093/bioinformatics/bty1049>, Nguyen et al. (2017)<DOI: 10.1101/gr.215129.116>, Nguyen et al. (2021)<DOI: 10.3389/fonc.2021.725133>).
RcppParallel, FNN, cluster, irlba, mclust, impute
Packaged: 2021-12-14 19:25:49 UTC; hungnguyen

Title: Estimation of the Probability of Informed Trading
c(person("Montasser", "Ghachem",, "montasser.ghachem@pinstimation.com", role = c("aut", "cre","cph"), comment = c(ORCID = "0000-0001-6991-3316")),
person("Oguz", "Ersan", ,"oguz.ersan@pinstimation.com", role = c("aut"), comment = c(ORCID = "0000-0003-3135-5317")))
Author: Montasser Ghachem [aut, cre, cph]
Description: 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.
Imports: Rdpack, knitr, methods, skellam, nloptr, furrr, future, dplyr,