package scientific.stats.continuous
import std.math.*
import std.unittest.*
import std.unittest.testmacro.*
import scientific.numbers.*
import scientific.stats.random.*
/*
* Log of Probability density function
*/
public func gengammaLogPDF(x: Float64, a: Float64, c: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y < 0.0) {
throw IllegalArgumentException("gengammaLogPDF: input value x out of bound.")
}
if (a <= 0.0 || c == 0.0) {
throw IllegalArgumentException("gengammaLogPDF: shape parameter out of bound.")
}
return log(abs(c)) + (a * c - 1.0) * log(y) - pow(y, c) - gammaLog(a) - log(scale)
}
/*
* Probability density function
*/
public func gengammaPDF(x: Float64, a: Float64, c: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y < 0.0) {
throw IllegalArgumentException("gengammaPDF: input value x out of bound.")
}
if (a <= 0.0 || c == 0.0) {
throw IllegalArgumentException("gengammaPDF: shape parameter out of bound.")
}
return exp(gengammaLogPDF(x, a, c, loc: loc, scale: scale))
}
/*
* Cumulative probability density function
*/
public func gengammaCDF(x: Float64, a: Float64, c: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y < 0.0) {
throw IllegalArgumentException("gengammaCDF: input value x out of bound.")
}
if (a <= 0.0 || c == 0.0) {
throw IllegalArgumentException("gengammaCDF: shape parameter out of bound.")
}
let t = pow(y, c)
let val1 = igam(a, t)
let val2 = 1.0 - igam(a, t)
var res = 0.0
if (c > 0.0) {
res = val1
} else {
res = val2
}
return res
}
/*
* Log of Cumulative probability density function
*/
public func gengammaLogCDF(x: Float64, a: Float64, c: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y < 0.0) {
throw IllegalArgumentException("gengammaLogCDF: input value x out of bound.")
}
if (a <= 0.0 || c == 0.0) {
throw IllegalArgumentException("gengammaLogCDF: shape parameter out of bound.")
}
let temp = gengammaCDF(x, a, c, loc: loc, scale: scale)
if (temp < 0.000001) {
throw IllegalArgumentException("gengammaLogCDF: return-value too small.")
}
return log(temp)
}
/*
* Sample
*/
public func gengammaSample(r: Random, a: Float64, c: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
if (a <= 0.0 || c == 0.0) {
throw IllegalArgumentException("gengammaSample: shape parameter out of bound.")
}
let r1 = gamSample(r, a)
let r2 = pow(r1, 1.0 / c)
return r2 * scale + loc
}
@Test
public class testGengamma {
@TestCase
func testGengamma(): Unit {
@Assert(approxEqual(gengammaLogPDF(2.0, 2.0, 3.0, loc: 1.0, scale: 2.0), -3.1852707946915624, atol:1e-13))
@Assert(approxEqual(gengammaLogCDF(2.0, 2.0, 3.0, loc: 1.0, scale: 2.0), -4.934927177496508, atol:1e-13))
}
}