person("Andreas", "Buchmueller", email = "a.buchmueller@stud.uni-goettingen.de", role = c("aut", "cre"),
person("Gillian", "Kant", email = "gillian.kant@stud.uni-goettingen.de", role = c("aut", "ths"),
person("Christoph", "Weisser", email = "c.weisser@uni-goettingen.de", role = c("aut", "ths"),
person("Benjamin", "Saefken", email = "benjamin.saefken@uni-goettingen.de", role = c("aut", "ths"),
person("Thomas", "Kneib", email = "thomas.kneib@wiwi.uni-goettingen.de", role = c("rev", "ths", "dgs"),
person("Krisztina", "Kis-Katos", email = "krisztina.kis-katos@uni-goettingen.de", role = "rev",
LDA and structural topic models (STM). Comes with visualizing capabilities like tweet and hashtag maps
stm, tidyr, rlang, maps, LDAvis, leaflet, ldatuning, stringi,
Suggests: rmarkdown, knitr, tidytext, modeltools, servr
Packaged: 2021-12-06 15:07:03 UTC; abuchmueller
Author: Andreas Buchmueller [aut, cre] (github.com/abuchmueller),
Christoph Weisser [aut, ths] (<https://orcid.org/0000-0003-0616-1027>),
Benjamin Saefken [aut, ths] (<https://orcid.org/0000-0003-4702-3333>),
Thomas Kneib [rev, ths, dgs] (<https://orcid.org/0000-0003-3390-0972>),

Description: 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.
Imports: curl, dplyr, jsonlite, lubridate, plyr, purrr, tibble,
twitteR, naptime, utils, tidytext, magrittr

Title: Simulate Survival Data for Randomized Clinical Trials
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"))
Description: 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.