Depends: R (>= 3.2.0), ape, corpcor, nloptr, geiger, RColorBrewer
Imports: igraph, numDeriv, phytools, paleotree, phangorn, stats, lhs,

Author: Jeremy M. Beaulieu <jmbeauli@uark.edu>, Brian O'Meara <bomeara@utk.edu>
Description: Estimates rates for continuous character evolution under Brownian motion and a new set of Ornstein-Uhlenbeck based Hansen models that allow both the strength of the pull and stochastic motion to vary across selective regimes. Beaulieu et al (2012).
Packaged: 2022-06-07 12:37:26 UTC; jeremybeaulieu

Authors@R: c(person(given = "Joseph", family = "Pane", role = c("aut", "cre"),
person(given = "Lane", family = "Burgette", role = "aut"),
person(given = "Beth Ann", family = "Griffin", role = "aut"),
person(given = "Daniel", family = "McCaffrey", role = "aut"))
Description: This tool was designed to assess the sensitivity of research findings to omitted variables when estimating causal effects using propensity score (PS) weighting. This tool produces graphics and summary results that will enable a researcher to quantify the impact an omitted variable would have on their results. Burgette et al. (2021) describe the methodology behind the primary function in this package, ov_sim. The method is demonstrated in Griffin et al. (2020) <doi:10.1016/j.jsat.2020.108075>.
Imports: Amelia, EnvStats, devtools, dplyr, ggplot2, ggrepel, glue,
magrittr, metR, purrr, progress, rlang, survey, stats, tibble,

Authors@R: c(person(given = "Lane", family = "Burgette", role = c("aut", "cre"),
person(given = "Joseph", family = "Pane", role = "aut"),

Title: Optimal Weight Exchange Algorithm for Optimal Designs for Three
person("Shuai", "Hao", email="shuaih0303@gmail.com", role = c("aut","cre")),
person("Min", "Yang", email="myang2@uic.edu", role = c("aut")),
person("Wei", "Zheng", email= "wzheng9@utk.edu", role = c("aut")))
Description: An implementation of optimal weight exchange algorithm Yang(2013) <doi:10.1080/01621459.2013.806268> for three models.
They are Crossover model with subject dropout, crossover model with proportional
first order residual effects and interference model. You can use it to find either
A-opt or D-opt approximate designs. Exact designs can be automatically rounded
from approximate designs and relative efficiency is provided as well.
Imports: gtools (>= 3.8.1), MASS, shiny (>= 1.1.0)