Author: Canhong Wen, Xueqin Wang, Yanhe Shen, Aijun Zhang
Description: An implementation of the fast structural filtering with L0 penalty. It includes an adaptive polynomial estimator by minimizing the least squares error with constraints on the number of breaks in their (k + 1)-st discrete derivative, for a chosen integer k >= 0. It also includes generalized structure sparsity constraint, i.e., graph trend filtering. This package is implemented via the primal dual active set algorithm, which formulates estimates and residuals as primal and dual variables, and utilizes efficient active set selection strategies based on the properties of the primal and dual variables.

Title: Power Hyperbolic Functions and Kiener Distributions
Description: A set of functions to manipulate power hyperbolas, power
hyperbolic functions and Kiener distributions of type I, II, III and IV
which exhibit left and right fat tails like those that occur in financial
markets. These distributions can be used to estimate with a high
accuracy market risks and value-at-risk.
Collate: 'FatTailsR-package.r' 'trigohp.R' 'logishp.R' 'conversion.R'
'kiener1.R' 'kiener2.R' 'kiener3.R' 'kiener4.R' 'regression.R'

Title: Kiener Distributions and Fat Tails in Finance
Description: Kiener distributions of type I, II, III and IV tailored to
distributions with left and right fat tails like those that occur
in financial markets. These distributions can be used to estimate
with a high accuracy market risks and value-at-risk. Also include power
hyperbolas and power hyperbolic functions.

Description: Kiener distributions K1, K2, K3 and K4 to characterize
distributions with left and right, symmetric or asymmetric fat tails in market
finance, neuroscience and other disciplines. Two algorithms to estimate with
a high accuracy distribution parameters, quantiles, value-at-risk and expected
shortfall. Also, power hyperbolas and power hyperbolic functions. This is a
major update that breaks compatibility with previous versions.
Collate: 'a_FatTailsR-package.R' 'b_data.R' 'c_trigohp.R' 'd_logishp.R'