Title: Fits Heterogeneous Panel Data Models
Description: Fits heterogeneous panel data models with interactive effects for linear regression, logistic, count, probit, quantile, and clustering. Based on Ando, T. and Bai, J. (2015) "A simple new test for slope homogeneity in panel data models with interactive effects" <doi: 10.1016/j.econlet.2015.09.019>, Ando, T. and Bai, J. (2015) "Asset Pricing with a General Multifactor Structure" <doi: 10.1093/jjfinex/nbu026> , Ando, T. and Bai, J. (2016) "Panel data models with grouped factor structure under unknown group membership" <doi: 10.1002/jae.2467>, Ando, T. and Bai, J. (2017) "Clustering huge number of financial time series: A panel data approach with high-dimensional predictors and factor structures" <doi: 10.1080/01621459.2016.1195743>, Ando, T. and Bai, J. (2020) "Quantile co-movement in financial markets" <doi: 10.1080/01621459.2018.1543598>, Ando, T., Bai, J. and Li, K. (2021) "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity" <doi: 10.1016/j.jeconom.2020.11.013.>.

Author: Javier Cabrera <xavier.cabrera@gmail.com>, Fei Wang <cherry8177@gmail.com>
Description: Building patient level networks for prediction of
medical outcomes and draw the cluster of network.
This package is based on paper Personalized disease
networks for understanding and predicting cardiovascular
(See Cabrera et al. <http://circ.ahajournals.org/content/134/Suppl_1/A14957>).
Imports: survival, glmnet, ggplot2, network

Title: PDQ Functions via Gram Charlier and Cornish Fisher
Description: A collection of tools for approximating the 'PDQ' functions (respectively, the
cumulative distribution, density, and quantile) of probability distributions via classical
expansions involving moments and cumulants.

Title: PDQ Functions via Gram Charlier, Edgeworth, and Cornish Fisher
Suggests: ggplot2, reshape2, testthat, knitr
Collate: 'cornish_fisher.r' 'edgeworth.r' 'gram_charlier.r' 'moments.r'

Description: A collection of tools for approximating the 'PDQ' functions
(respectively, the cumulative distribution, density, and quantile) of
probability distributions via classical expansions involving moments and