Suggests: dse, expsmooth, fBasics, fGarch, forecast, polynom,

Title: Casualty Actuarial Society Individual Claim Simulator
person("Robert", "Bear", email = "rbear@reserveprism.com", role = "aut"),
person("Kailan", "Shang", email = "klshang81@gmail.com", role = c("aut","cre")),
person("Hai", "You", email = "hyou@reserveprism.com", role = "aut"),
person("Brian", "Fannin", email = "bfannin@casact.org", role = "ctb"))
Description: It is an open source insurance claim simulation engine sponsored
by the Casualty Actuarial Society. It generates individual insurance claims
including open claims, reopened claims, incurred but not reported claims
and future claims. It also includes claim data fitting functions to help set
simulation assumptions. It is useful for claim level reserving analysis.
Imports: parallel, R2HTML, fitdistrplus, moments, copula,

Title: Identify similar cases for qualitative case studies.
Description: This package allows users to identify similar cases for qualitative case studies using statistical matching methods.
Packaged: 2014-09-05 17:14:16 UTC; Richard Nielsen

Title: Identify Similar Cases for Qualitative Case Studies
Description: Allows users to identify similar cases for qualitative case studies using statistical matching methods.

Packaged: 2017-01-06 17:20:22 UTC; Richard Nielsen

Packaged: 2019-12-12 19:50:51 UTC; Richard Nielsen

Packaged: 2014-06-24 21:52:32 UTC; Richard Nielsen

Title: Fitting Flexible Smooth-in-Time Hazards and Risk Functions via
person("Sahir", "Bhatnagar", email = "sahir.bhatnagar@gmail.com",
role = c("aut", "cre"), comment = "http://sahirbhatnagar.com/"),
person("Maxime", "Turgeon", email = "maxime.turgeon@mail.mcgill.ca",
role = c("aut"), comment = "http://turgeonmaxime.github.io/"),
person("Olli", "Saarela", email = "olli.saarela@utoronto.ca",
role = c("aut"), comment = "http://individual.utoronto.ca/osaarela/"),
person("James", "Hanley", email = "james.hanley@mcgill.ca",
role = c("aut"), comment = "http://www.medicine.mcgill.ca/epidemiology/hanley/")
Description: Implements the case-base sampling approach of Hanley and Miettinen (2009) <DOI:10.2202/1557-4679.1125>,
Saarela and Arjas (2015) <DOI:10.1111/sjos.12125>, and Saarela (2015) <DOI:10.1007/s10985-015-9352-x>, for fitting flexible hazard
regression models to survival data with single event type or multiple competing causes via logistic and multinomial regression.
From the fitted hazard function, cumulative incidence, risk functions of time, treatment and profile
can be derived. This approach accommodates any log-linear hazard function of prognostic time, treatment,
and covariates, and readily allows for non-proportionality. We also provide a plot method for visualizing
incidence density via population time plots.
Imports: data.table, ggplot2, methods, survival, VGAM
Suggests: eha, knitr, rmarkdown, splines, testthat
Author: Sahir Bhatnagar [aut, cre] (http://sahirbhatnagar.com/),