Suggests: moments, distrEx, tseries, urca, lmtest, sandwich, psych,
GPArotation, chron, polynom, fUnitRoots, e1071

Analysis of Financial Time Series, second edition (Wiley).

Title: Financial Instrument Model Infrastructure for R
Author: Peter Carl, Dirk Eddelbuettel, Jeffrey Ryan, Joshua Ulrich,
Description: Infrastructure for defining meta-data and relationships
'redenominate.R' 'splice.R' 'splooth.R' 'synthetic.R' 'volep.R'

Author: Peter Carl, Brian G. Peterson, Garrett See
Description: Infrastructure for defining meta-data and
Suggests: foreach, XML (>= 3.96.1.1), testthat, its, timeSeries

Title: Financial Instrument Model Infrastructure and Meta-Data
Suggests: foreach, XML (>= 3.96.1.1), testthat, timeSeries

Title: Financial Mathematics for Actuaries
Authors@R: c(person("Kameron", "Penn", email = "rfinancialmathpkg@gmail.com",role = c("aut", "cre")),person("Jack", "Schmidt", email = "rfinancialmathpkg@gmail.com",role = "aut"))
Description: 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.

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

Title: Find all root(s) of the equation and Find root(s) of the
Author: Bingpei Wu & Jiajun He & Sijie Chen & Yangyang Liu
Description: 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.
Packaged: 2012-07-23 04:56:37 UTC; Administrator

Title: R Package for Finding Heterogeneous Treatment Effects
Description: 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.