Peter Carl, Brian G. Peterson, Garrett See
Infrastructure for defining meta-data and
relationships for financial instruments.
foreach, XML (>= 3.96.1.1), testthat, its, timeSeries

Financial Instrument Model Infrastructure and Meta-Data
c(
person(given=c("Brian","G."),family="Peterson",role=c("aut","cph"),
email="brian@braverock.com") ,
person(given="Peter",family="Carl",role=c("aut","cph"),
email="peter@braverock.com") ,
person(given="Garett",family="See",role=c("aut","cph")) ,
person(given="Ross",family="Bennett",role=c("ctb","cre"),
email="rossbennett34@gmail.com") ,
person(given="Lance",family="Levenson",role=c("ctb")),
person(given="Ilya",family="Kipnis",role=c("ctb")),
person(given="Alex",family="Petitt",role=c("ctb"))
)
foreach, XML (>= 3.96.1.1), testthat, timeSeries
Brian G. Peterson [aut, cph],
Peter Carl [aut, cph],
Garett See [aut, cph],
Ross Bennett [ctb, cre],
Lance Levenson [ctb],
Ilya Kipnis [ctb],
Alex Petitt [ctb]

c(person("Kameron", "Penn", email = "rfinancialmathpkg@gmail.com",role = c("aut", "cre")),person("Jack", "Schmidt", email = "rfinancialmathpkg@gmail.com",role = "aut"))
Kameron Penn [aut, cre],
Jack Schmidt [aut]
Contains financial math functions and introductory derivative functions included in the Society of Actuaries and Casualty Actuarial Society 'Financial Mathematics' exam, and some topics in the 'Models for Financial Economics' exam.

c(person("Kameron", "Penn", email = "kameron.penn.financialmath@gmail.com",role = c("aut", "cre")),person("Jack", "Schmidt",role = "aut"))

Find all root(s) of the equation and Find root(s) of the
equation by dichotomy
Bingpei Wu & Jiajun He & Sijie Chen & Yangyang Liu
Find all root(s) of the equation,including complex
roots;Find root(s) of the equation by dichotomy.Besides,in
dichotomy, more than one interval can be given at a time.

R Package for Finding Heterogeneous Treatment Effects
Marc Ratkovic <ratkovic@princeton.edu>, Kosuke Imai
<kimai@princeton.edu>,
FindIt is an R package that implements the heterogeneous
treatment effect estimation procedure proposed by Imai and
Ratkovic (2012).  The method assumes a binary outcome, coded
+/- 1, and a treatment variable, code 0/1, with a set of
pre-treatment covariates.  Through the use of one LASSO
constraint over the treatment parameters of interest and
another over the pretreatment covariates, the method directly
targets the heterogeneous treatment effects of interest.