Model Free Approach to Quantifying Surrogacy
c(
person("Xuan", "Wang", role = "aut"),
person("Layla", "Parast", role = c("aut", "cre"), email = "parast@austin.utexas.edu"),
person("Ming", "Yang", role = "aut"),
person("Lu", "Tian", role = "aut"),
person("Tianxi", "Cai", role = "aut")
)
Identifies an optimal transformation of a surrogate marker such that the proportion of treatment effect explained can be inferred based on the transformation of the surrogate and nonparametrically estimates two model-free quantities of this proportion. Details are described in Wang et al (2020) <doi:10.1093/biomet/asz065>.
Xuan Wang [aut],
Layla Parast [aut, cre],
Ming Yang [aut],
Lu Tian [aut],
Tianxi Cai [aut]

Xiao Lin <xlin3@mdanderson.org>, Xuelin Huang<xlhuang@mdanderson.org>
Identify the optimal timing for new treatment initiation during multiple state disease transition, including  multistate model fitting, simulation of mean residual lifetime for a given transition state, and estimation of confidence interval. The method is referred to de Wreede, L., Fiocco, M., & Putter, H. (2011) <doi:10.18637/jss.v038.i07>.

Option Pricing with Efficient Simulation Algorithms
Efficient Monte Carlo Algorithms for the price and the sensitivities of Asian and European Options under Geometric Brownian Motion.

This package estimates a mix of lognormal distributions from
interest-rate option data.
This package provides the estimation of implied
probability density functions (pdf) from options data. The
pdf's take the form of a mix of lognormal distributions. The
methods used in the routines are discussed in the paper:
Soderlind, P., and L. E. O. Svensson (1997), "New Techniques to
Extract Market Expectations from Financial Instruments",
Journal of Monetary Economics, 40, 383-429.  The user should
kindly notice that this package is the R port of the Matlab
routines originally distributed by P. Soderlind, and freely
available from: http://home.datacomm.ch/paulsoderlind/

c(
person("Florian", "Detsch", role = c("cre", "aut"), email = "fdetsch@web.de"),
person("Tim", "Appelhans", role = "ctb"),
person("Baptiste", "Auguie", role = "ctb"),
person("OpenStreetMap contributors", role = "cph"))
I tend to repeat the same code chunks over and over again. At
first, this was fine for me and I paid little attention to such redundancies.
A little later, when I got tired of manually replacing Linux filepaths with
the referring Windows versions, and vice versa, I started to stuff some very
frequently used work-steps into functions and, even later, into a proper R
package. And that's what this package is - a hodgepodge of various R functions
meant to simplify (my) everyday-life coding work without, at the same time,
being devoted to a particular scope of application.
bookdown, devtools, grDevices, grid, knitr, lattice,
latticeExtra, plotrix, Rcpp (>= 0.11.3), rgdal, sf, sp, stats
Florian Detsch [cre, aut],
Tim Appelhans [ctb],
Baptiste Auguie [ctb],
OpenStreetMap contributors [cph]