package scientific.stats.continuous
import std.math.*
import std.unittest.*
import std.unittest.testmacro.*
import scientific.numbers.*
import scientific.stats.normal.*
import scientific.stats.random.*
/*
* Log of Probability density function
*/
public func fatiguelifeLogPDF(x: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y < 0.0) {
throw IllegalArgumentException("fatiguelifeLogPDF: input value out of bound.")
}
if (k <= 0.0) {
throw IllegalArgumentException("fatiguelifeLogPDF: shape parameter out of bound.")
}
let temp = -(y - 1.0) * (y - 1.0) / (2.0 * y * k * k)
return log(1.0 + y) - log(2.0 * k) - 0.5 * log(2.0 * Float64.getPI()) - 1.5 * log(y) + temp - log(scale)
}
/*
* Probability density function
*/
public func fatiguelifePDF(x: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y < 0.0) {
throw IllegalArgumentException("fatiguelifePDF: input value out of bound.")
}
if (k <= 0.0) {
throw IllegalArgumentException("fatiguelifePDF: shape parameter out of bound.")
}
return exp(fatiguelifeLogPDF(x, k, loc: loc, scale: scale))
}
/*
* Cumulative probability density function
*/
public func fatiguelifeCDF(x: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y < 0.0) {
throw IllegalArgumentException("fatiguelifeCDF: input value x out of bound.")
}
if (k <= 0.0) {
throw IllegalArgumentException("fatiguelifeCDF: shape parameter out of bound.")
}
let temp = 1.0 / k * (sqrt(y) - 1.0 / sqrt(y))
return normalCDF(temp)
}
/*
* Log of Cumulative probability density function
*/
public func fatiguelifeLogCDF(x: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y < 0.0) {
throw IllegalArgumentException("fatiguelifeLogCDF: input value x out of bound.")
}
if (k <= 0.0) {
throw IllegalArgumentException("fatiguelifeLogCDF: shape parameter out of bound.")
}
let temp = fatiguelifeCDF(x, k, loc: loc, scale: scale)
if (temp < 0.000001) {
throw IllegalArgumentException("fatiguelifeLogCDF: return-value too small.")
}
return log(temp)
}
/*
* ppf
*/
public func fatiguelifePPF(q: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
if (q <= 0.0 || q >= 1.0) {
throw IllegalArgumentException("fatiguelifePPF: quantile out of bound.")
}
if (k <= 0.0) {
throw IllegalArgumentException("fatiguelifePPF: shape parameter out of bound.")
}
let temp = k * normalPPF(q)
let t = temp + sqrt(temp * temp + 4.0)
return (0.25 * t * t) * scale + loc
}
/*
* Mean of the distribution.
*/
public func fatiguelifeMean(k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
if (k <= 0.0) {
throw IllegalArgumentException("fatiguelifeMean: shape parameter out of bound.")
}
return (0.5 * k * k + 1.0) * scale + loc
}
/*
* Var of the distribution.
*/
public func fatiguelifeVar(k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
if (k <= 0.0) {
throw IllegalArgumentException("fatiguelifeVar: shape parameter out of bound.")
}
let temp = 5.0 * k * k + 4.0
return temp * k * k / 4.0 * scale * scale
}
/*
* Std of the distribution.
*/
public func fatiguelifeStd(k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
if (k <= 0.0) {
throw IllegalArgumentException("fatiguelifeStd: shape parameter out of bound.")
}
return sqrt(fatiguelifeVar(k, loc: loc, scale: scale))
}
@Test
public class TestFatigueLife {
@TestCase
func testFatiguelife(): Unit {
@Assert(approxEqual(fatiguelifeLogPDF(2.0, 2.0, loc: 1.0, scale: 2.0), -1.6156941959364262, atol:1e-13))
@Assert(approxEqual(fatiguelifeLogCDF(2.0, 2.0, loc: 1.0, scale: 2.0), -1.0165619839535647, atol:1e-13))
@Assert(approxEqual(fatiguelifePPF(0.2, 2.0, loc: 1.0, scale: 2.0), 1.4332098420421369, atol:1e-9))
@Assert(approxEqual(fatiguelifeMean(2.0, loc: 1.0, scale: 2.0), 7.0, atol:1e-13))
@Assert(approxEqual(fatiguelifeVar(2.0, loc: 1.0, scale: 2.0), 96.0, atol:1e-13))
}
}