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 halfgennormLogPDF(x: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y <= 0.0) {
throw IllegalArgumentException("halfgennormLogPDF: input value out of bound.")
}
return log(k) - gammaLog(1.0 / k) - pow(abs(y), k) - log(scale)
}
/*
* Probability density function
*/
public func halfgennormPDF(x: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y <= 0.0) {
throw IllegalArgumentException("halfgennormPDF: input value out of bound.")
}
let temp = halfgennormLogPDF(x, k, loc:loc, scale: scale)
return exp(temp)
}
/*
* Cumulative probability density function
*/
public func halfgennormCDF(x: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y <= 0.0) {
throw IllegalArgumentException("halfgennormCDF: input value out of bound.")
}
return igam(1.0 / k, pow(y, k))
}
/*
* Log of Cumulative probability density function
*/
public func halfgennormLogCDF(x: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
let y = (x - loc) / scale
if (y <= 0.0) {
throw IllegalArgumentException("halfgennormLogCDF: input value out of bound.")
}
let temp = halfgennormCDF(x, k, loc: loc, scale: scale)
if (temp < 0.000001) {
throw IllegalArgumentException("halfgennormLogCDF: return-value too small.")
}
return log(temp)
}
/*
* ppf
*/
public func halfgennormPPF(q: Float64, k: Float64, loc!: Float64 = 0.0, scale!: Float64 = 1.0): Float64 {
if (q <= 0.0 || q >= 1.0) {
throw IllegalArgumentException("halfgennormPPF: quantile out of bound.")
}
let temp = igami(1.0 / k, 1.0 - q)
let res = pow(temp, 1.0 / k)
return res * scale + loc
}
@Test
public class TsetHalfgennorm {
@TestCase
func testHalfgennorm(): Unit {
@Assert(approxEqual(halfgennormLogPDF(2.0, 2.0, loc: 1.0, scale: 2.0), -0.8223649429247, atol:1e-13))
@Assert(approxEqual(halfgennormLogCDF(2.0, 2.0, loc: 1.0, scale: 2.0), -0.652965625676331, atol:1e-13))
@Assert(approxEqual(halfgennormPPF(0.2, 2.0, loc: 1.0, scale: 2.0), 1.3582869092425833, atol:1e-13))
}
}