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.
'a_FatTailsR-package.R' 'b_data.R' 'c_trigohp.R' 'd_logishp.R'
'e_conversion.R' 'f_kiener1.R' 'g_kiener2.R' 'h_kiener3.R'
'i_kiener4.R' 'j_moments.R' 'k_tailskiener.R' 'l_estimation.R'
'm_laplaceroll.R' 'n_estimation2.R' 'o_regression.R'

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. Some functions
introduced in v1.2-0 were suppressed.

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. v1.5-5
corresponds to upgrade from 3.1.0 to R-3.2.3.

Kiener distributions K1, K2, K3, K4 and K7 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. Include power hyperbolas and power hyperbolic functions.
minpack.lm, timeSeries, parallel, methods, stats
'a_FatTailsR-package.R' 'b_data.R' 'c_trigohp.R' 'd_logishp.R'
'e_conversion.R' 'f_kiener1.R' 'g_kiener2.R' 'h_kiener3.R'
'i_kiener4.R' 'j_kiener7.R' 'k_kienerES.R' 'l_moments.R'
'm_laplaceroll.R' 'n_estimation.R' 'o_estimation2.R'
'p_regression.R'