Title: Epistasis Test in Meta-Analysis (ETMA)
Description: Traditional meta-regression based method has been developed for using meta-analysis data, but it faced the challenge of inconsistent estimates. This package purpose a new statistical method to detect epistasis using incomplete information summary, and have proven it not only successfully let consistency of evidence, but also increase the power compared with traditional method.

Description: Traditional meta-regression based method has been developed for using meta-analysis data, but it faced the challenge of inconsistent estimates. This package purpose a new statistical method to detect epistasis using incomplete information summary, and have proven it not only successfully let consistency of evidence, but also increase the power compared with traditional method (Detailed tutorial is shown in website <http://rpubs.com/chinlin/ETMA>).

Description: Traditional meta-regression based method has been developed for using meta-analysis data, but it faced the challenge of inconsistent estimates. This package purpose a new statistical method to detect epistasis using incomplete information summary, and have proven it not only successfully let consistency of evidence, but also increase the power compared with traditional method (Detailed tutorial is shown in website).

Description: Use R to interface with the 'ETRADE' API <https://developer.etrade.com/home>.
Functions include authentication, trading, quote requests, account information, and option
chains. A user will need an ETRADE brokerage account and 'ETRADE' API approval. See README
for authentication process and examples.
Imports: magrittr, httr, urltools, dplyr, rvest, purrr, jsonlite

Title: Classification and Regression with Structured and Mixed-Type
Description: Implementation of Energy Trees, a statistical model to perform
classification and regression with structured and mixed-type data. The
model has a similar structure to Conditional Trees, but brings in Energy
Statistics to test independence between variables that are possibly
structured and of different nature. Currently, the package covers functions
and graphs as structured covariates. It builds upon 'partykit' to
provide functionalities for fitting, printing, plotting, and predicting with
Energy Trees. Energy Trees are described in Giubilei et al. (2022)
Imports: brainGraph, cluster, energy, fda.usc (>= 2.0.0), igraph,
NetworkDistance, parallel, partykit, survival, TDA, usedist
Suggests: knitr, MLmetrics, rmarkdown, testthat (>= 3.0.0)
Author: Riccardo Giubilei [aut, cre] (<https://orcid.org/0000-0002-1674-4886>),
Achim Zeileis [ctb] (<https://orcid.org/0000-0003-0918-3766>, (partykit