public static double inverseCumulativeNormalDistribution_Wichura(double p) {
		double zero = 0.e+00, one = 1.e+00, half = 0.5e+00;
		double split1 = 0.425e+00, split2 = 5.e+00;
		double const1 = 0.180625e+00, const2 = 1.6e+00;

		//  coefficients for p close to 0.5
		double a0 = 3.3871328727963666080e+00;
		double a1 = 1.3314166789178437745e+02;
		double a2 = 1.9715909503065514427e+03;
		double a3 = 1.3731693765509461125e+04;
		double a4 = 4.5921953931549871457e+04;
		double a5 = 6.7265770927008700853e+04;
		double a6 = 3.3430575583588128105e+04;
		double a7 = 2.5090809287301226727e+03;
		double b1 = 4.2313330701600911252e+01;
		double b2 = 6.8718700749205790830e+02;
		double b3 = 5.3941960214247511077e+03;
		double b4 = 2.1213794301586595867e+04;
		double b5 = 3.9307895800092710610e+04;
		double b6 = 2.8729085735721942674e+04;
		double b7 = 5.2264952788528545610e+03;
		//  hash sum ab 55.8831928806149014439

		//  coefficients for p not close to 0, 0.5 or 1.
		double c0 = 1.42343711074968357734e+00;
		double c1 = 4.63033784615654529590e+00;
		double c2 = 5.76949722146069140550e+00;
		double c3 = 3.64784832476320460504e+00;
		double c4 = 1.27045825245236838258e+00;
		double c5 = 2.41780725177450611770e-01;
		double c6 = 2.27238449892691845833e-02;
		double c7 = 7.74545014278341407640e-04;
		double d1 = 2.05319162663775882187e+00;
		double d2 = 1.67638483018380384940e+00;
		double d3 = 6.89767334985100004550e-01;
		double d4 = 1.48103976427480074590e-01;
		double d5 = 1.51986665636164571966e-02;
		double d6 = 5.47593808499534494600e-04;
		double d7 = 1.05075007164441684324e-09;
		//  hash sum cd 49.33206503301610289036

		//  coefficients for p near 0 or 1.
		double e0 = 6.65790464350110377720e+00;
		double e1 = 5.46378491116411436990e+00;
		double e2 = 1.78482653991729133580e+00;
		double e3 = 2.96560571828504891230e-01;
		double e4 = 2.65321895265761230930e-02;
		double e5 = 1.24266094738807843860e-03;
		double e6 = 2.71155556874348757815e-05;
		double e7 = 2.01033439929228813265e-07;
		double f1 = 5.99832206555887937690e-01;
		double f2 = 1.36929880922735805310e-01;
		double f3 = 1.48753612908506148525e-02;
		double f4 = 7.86869131145613259100e-04;
		double f5 = 1.84631831751005468180e-05;
		double f6 = 1.42151175831644588870e-07;
		double f7 = 2.04426310338993978564e-15;
		//  hash sum ef 47.52583 31754 92896 71629

		double q = p - half;
		double r, ppnd16;

		if (Math.abs(q) <= split1) {
			r = const1 - q * q;
			return q
					* (((((((a7 * r + a6) * r + a5) * r + a4) * r + a3) * r + a2) * r + a1) * r + a0)
					/ (((((((b7 * r + b6) * r + b5) * r + b4) * r + b3) * r + b2) * r + b1) * r + one);
		} else {
			if (q < zero) {
				r = p;
			} else {
				r = one - p;
			}

			if (r <= zero) {
				return zero;
			}
			r = Math.sqrt(-Math.log(r));
			if (r <= split2) {
				r -= const2;
				ppnd16 =
						(((((((c7 * r + c6) * r + c5) * r + c4) * r + c3) * r + c2) * r + c1) * r + c0)
						/ (((((((d7 * r + d6) * r + d5) * r + d4) * r + d3) * r + d2) * r + d1) * r + one);
			} else {
				r -= split2;
				ppnd16 =
						(((((((e7 * r + e6) * r + e5) * r + e4) * r + e3) * r + e2) * r + e1) * r + e0)
						/ (((((((f7 * r + f6) * r + f5) * r + f4) * r + f3) * r + f2) * r + f1) * r + one);
			}
			if (q < zero) {
				ppnd16 = -ppnd16;
			}

			return ppnd16;
		}
	}
public static double inverseCumulativeNormalDistribution_Wichura ( double p ) { double zero = 0.e+00 , one = 1.e+00 , half = 0.5e+00 ; double split1 = 0.425e+00 , split2 = 5.e+00 ; double const1 = 0.180625e+00 , const2 = 1.6e+00 ; double a0 = 3.3871328727963666080e+00 ; double a1 = 1.3314166789178437745e+02 ; double a2 = 1.9715909503065514427e+03 ; double a3 = 1.3731693765509461125e+04 ; double a4 = 4.5921953931549871457e+04 ; double a5 = 6.7265770927008700853e+04 ; double a6 = 3.3430575583588128105e+04 ; double a7 = 2.5090809287301226727e+03 ; double b1 = 4.2313330701600911252e+01 ; double b2 = 6.8718700749205790830e+02 ; double b3 = 5.3941960214247511077e+03 ; double b4 = 2.1213794301586595867e+04 ; double b5 = 3.9307895800092710610e+04 ; double b6 = 2.8729085735721942674e+04 ; double b7 = 5.2264952788528545610e+03 ; double c0 = 1.42343711074968357734e+00 ; double c1 = 4.63033784615654529590e+00 ; double c2 = 5.76949722146069140550e+00 ; double c3 = 3.64784832476320460504e+00 ; double c4 = 1.27045825245236838258e+00 ; double c5 = 2.41780725177450611770e-01 ; double c6 = 2.27238449892691845833e-02 ; double c7 = 7.74545014278341407640e-04 ; double d1 = 2.05319162663775882187e+00 ; double d2 = 1.67638483018380384940e+00 ; double d3 = 6.89767334985100004550e-01 ; double d4 = 1.48103976427480074590e-01 ; double d5 = 1.51986665636164571966e-02 ; double d6 = 5.47593808499534494600e-04 ; double d7 = 1.05075007164441684324e-09 ; double e0 = 6.65790464350110377720e+00 ; double e1 = 5.46378491116411436990e+00 ; double e2 = 1.78482653991729133580e+00 ; double e3 = 2.96560571828504891230e-01 ; double e4 = 2.65321895265761230930e-02 ; double e5 = 1.24266094738807843860e-03 ; double e6 = 2.71155556874348757815e-05 ; double e7 = 2.01033439929228813265e-07 ; double f1 = 5.99832206555887937690e-01 ; double f2 = 1.36929880922735805310e-01 ; double f3 = 1.48753612908506148525e-02 ; double f4 = 7.86869131145613259100e-04 ; double f5 = 1.84631831751005468180e-05 ; double f6 = 1.42151175831644588870e-07 ; double f7 = 2.04426310338993978564e-15 ; double q = p - half ; double r , ppnd16 ; if ( Math . abs ( q ) <= split1 ) { r = const1 - q * q ; return q * ( ( ( ( ( ( ( a7 * r + a6 ) * r + a5 ) * r + a4 ) * r + a3 ) * r + a2 ) * r + a1 ) * r + a0 ) / ( ( ( ( ( ( ( b7 * r + b6 ) * r + b5 ) * r + b4 ) * r + b3 ) * r + b2 ) * r + b1 ) * r + one ) ; } else { if ( q < zero ) { r = p ; } else { r = one - p ; } if ( r <= zero ) { return zero ; } r = Math . sqrt ( - Math . log ( r ) ) ; if ( r <= split2 ) { r -= const2 ; ppnd16 = ( ( ( ( ( ( ( c7 * r + c6 ) * r + c5 ) * r + c4 ) * r + c3 ) * r + c2 ) * r + c1 ) * r + c0 ) / ( ( ( ( ( ( ( d7 * r + d6 ) * r + d5 ) * r + d4 ) * r + d3 ) * r + d2 ) * r + d1 ) * r + one ) ; } else { r -= split2 ; ppnd16 = ( ( ( ( ( ( ( e7 * r + e6 ) * r + e5 ) * r + e4 ) * r + e3 ) * r + e2 ) * r + e1 ) * r + e0 ) / ( ( ( ( ( ( ( f7 * r + f6 ) * r + f5 ) * r + f4 ) * r + f3 ) * r + f2 ) * r + f1 ) * r + one ) ; } if ( q < zero ) { ppnd16 = - ppnd16 ; } return ppnd16 ; } }
Inverse of the cumulative distribution function of the standard normal distribution

Java Version of

Michael J. Wichura: Algorithm AS241 Appl. Statist. (1988) Vol. 37, No. 3 Produces the normal
deviate z corresponding to a given lower tail area of p; z is accurate
to about 1 part in 10**16.

The hash sums below are the sums of the mantissas of the coefficients.
they are included for use in checking transcription.

@param p The probablity (quantile).
@return The argument of the cumulative distribution function being assigned to p.