Provides an integration to the 'metatrader 5'.
The functionalities carry out automated trading using
sentiment indexes computed from 'twitter' and/or 'stockwits'.
The sentiment indexes are based on the ph.d. dissertation
"Essays on Economic Forecasting Models" (Godeiro,2018) <https://repositorio.ufpb.br/jspui/handle/123456789/15198>
The integration between the 'R' and the 'metatrader 5' allows sending buy/sell orders to the brokerage.
curl, dplyr, jsonlite, lubridate, plyr, purrr, tibble,
twitteR, naptime, utils, tidytext, magrittr

Simulate Survival Data for Randomized Clinical Trials
c(
person("Bo", "Zhang", email = "bzhang@pumabiotechnology.com", role = c("cre","aut")),
person("Yi", "Zhong", email = "yi.zhong1006@gmail.com", role = c("aut","ctb")),
person("Ginny", "Peng", email = "gpeng@pumabiotechnology.com", role = c("aut","ctb")),
person("Bin", "Yao", email = "BYao@pumabiotechnology.com", role = c("aut","ctb"))
)
A system to simulate clinical trials with time to event endpoints. Event simulation is based on Cox models allowing for covariates in addition to the treatment or group factor. Specific drop-out rates (separate from administrative censoring) can be controlled in the simulation. Other features include stratified randomization, non-proportional hazards, different accrual patterns, and event projection (timing to reach the target event) based on interim data.
Bo Zhang [cre, aut],
Yi Zhong [aut, ctb],
Ginny Peng [aut, ctb],
Bin Yao [aut, ctb]

Nonparametric test of equality between two copulas
Bruno Remillard and Jean-Francois Plante
This package implements the nonparametric test of equality
between two copulas proposed by Remillard and Scaillet in their
2009 JMVA paper.

Semiparametric Estimation Exploiting Covariate
Independence in Two-Phase Randomized Trials

Estimation of gene-treatment interactions in randomized clinical trials exploiting gene-treatment independence.

Estimate Gene-Treatment Interaction Exploiting Randomization

Estimation of gene-treatment interactions in randomized clinical trials exploiting gene-treatment independence. Methods used in the package refer to J. Y. Dai, M. LeBlanc, and C. Kooperberg (2009) Biometrics <doi:10.1111/j.1541-0420.2008.01046.x>.