Compute the quantile function for the normal distribution. - like Excel NORMINV

norminv.js

/// Original C++ implementation found at http://www.wilmott.com/messageview.cfm?catid=10&threadid=38771
/// C# implementation found at http://weblogs.asp.net/esanchez/archive/2010/07/29/a-quick-and-dirty-implementation-of-excel-norminv-function-in-c.aspx
/*
 *     Compute the quantile function for the normal distribution.
 *
 *     For small to moderate probabilities, algorithm referenced
 *     below is used to obtain an initial approximation which is
 *     polished with a final Newton step.
 *
 *     For very large arguments, an algorithm of Wichura is used.
 *
 *  REFERENCE
 *
 *     Beasley, J. D. and S. G. Springer (1977).
 *     Algorithm AS 111: The percentage points of the normal distribution,
 *     Applied Statistics, 26, 118-121.
 *
 *      Wichura, M.J. (1988).
 *      Algorithm AS 241: The Percentage Points of the Normal Distribution.
 *      Applied Statistics, 37, 477-484.
 */

function normsInv(p, mu, sigma)
{
    if (p < 0 || p > 1)
    {
        throw "The probality p must be bigger than 0 and smaller than 1";
    }
    if (sigma < 0)
    {
        throw "The standard deviation sigma must be positive";
    }

    if (p == 0)
    {
        return -Infinity;
    }
    if (p == 1)
    {
        return Infinity;
    }
    if (sigma == 0)
    {
        return mu;
    }

    var q, r, val;

    q = p - 0.5;

    /*-- use AS 241 --- */
    /* double ppnd16_(double *p, long *ifault)*/
    /*      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.
    */
    if (Math.abs(q) <= .425)
    {/* 0.075 <= p <= 0.925 */
        r = .180625 - q * q;
        val =
               q * (((((((r * 2509.0809287301226727 +
                          33430.575583588128105) * r + 67265.770927008700853) * r +
                        45921.953931549871457) * r + 13731.693765509461125) * r +
                      1971.5909503065514427) * r + 133.14166789178437745) * r +
                    3.387132872796366608)
               / (((((((r * 5226.495278852854561 +
                        28729.085735721942674) * r + 39307.89580009271061) * r +
                      21213.794301586595867) * r + 5394.1960214247511077) * r +
                    687.1870074920579083) * r + 42.313330701600911252) * r + 1);
    }
    else
    { /* closer than 0.075 from {0,1} boundary */

        /* r = min(p, 1-p) < 0.075 */
        if (q > 0)
            r = 1 - p;
        else
            r = p;

        r = Math.sqrt(-Math.log(r));
        /* r = sqrt(-log(r))  <==>  min(p, 1-p) = exp( - r^2 ) */

        if (r <= 5)
        { /* <==> min(p,1-p) >= exp(-25) ~= 1.3888e-11 */
            r += -1.6;
            val = (((((((r * 7.7454501427834140764e-4 +
                       .0227238449892691845833) * r + .24178072517745061177) *
                     r + 1.27045825245236838258) * r +
                    3.64784832476320460504) * r + 5.7694972214606914055) *
                  r + 4.6303378461565452959) * r +
                 1.42343711074968357734)
                / (((((((r *
                         1.05075007164441684324e-9 + 5.475938084995344946e-4) *
                        r + .0151986665636164571966) * r +
                       .14810397642748007459) * r + .68976733498510000455) *
                     r + 1.6763848301838038494) * r +
                    2.05319162663775882187) * r + 1);
        }
        else
        { /* very close to  0 or 1 */
            r += -5;
            val = (((((((r * 2.01033439929228813265e-7 +
                       2.71155556874348757815e-5) * r +
                      .0012426609473880784386) * r + .026532189526576123093) *
                    r + .29656057182850489123) * r +
                   1.7848265399172913358) * r + 5.4637849111641143699) *
                 r + 6.6579046435011037772)
                / (((((((r *
                         2.04426310338993978564e-15 + 1.4215117583164458887e-7) *
                        r + 1.8463183175100546818e-5) * r +
                       7.868691311456132591e-4) * r + .0148753612908506148525)
                     * r + .13692988092273580531) * r +
                    .59983220655588793769) * r + 1);
        }

        if (q < 0.0)
        {
            val = -val;
        }
    }

    return mu + sigma * val;
}


// normInv(0.2, 3.5, 0.707106781);

Thank you very much! Add another language to it (java): http://info.michael-simons.eu/2013/02/21/java-implementation-of-excels-statistical-functions-norminv/

Thanks for your work!
There's a typing error in this example that prevents it from running. Row 81: replace Math.Sqrt with Math.sqrt

// normInv(0.2, 3.5, 0,707106781);
A minor thing: the last number has a comma while it should be a dot?

It's Math.sqrtnot Math.Sqrt. Thank you for the snippet.

thank you very much, did you know for gumbelinv(), loginv(), logpersoninv() && normaldist(), gumbeldist(), logdist(), logpersondist() ?
I waiting your answer :)

@dginanjar13, I've used some of them but not in JavaScript and have no use for them.