/*-Algorithm AS 177 * Expected Normal Order Statistics (Exact and Approximate), * by J.P. Royston, 1982. * Applied Statistics, 31(2):161-165. * * Translation to C by James Darrell McCauley, mccauley@ecn.purdue.edu. * * The functions nscor1() and nscor2() calculate the expected values of * normal order statistics in exact or approximate form, respectively. * */ #define NSTEP 721 #define H 0.025 #include #include void nscor1 (double s[], int n, int n2, double work[], int *ifault) /* exact calculation of normal scores */ { double ani, c, c1, d, scor, alnfac(); int i,j; *ifault = 3; if (n2 != n / 2) return; *ifault = 1; if (n <= 1) return; *ifault = 0; if (n > 2000) *ifault = 2; /* calculate the natural log of factorial(n) */ c1 = alnfac (n); d = c1 - log ((double) n); /* accumulate ordinates for calculation of integral for rankits */ for (i = 0; i < n2; ++i) { ani = (double) n - i - 1; c = c1 - d; for (scor=0.0, j = 0; j < NSTEP; ++j) scor += work[0*NSTEP+j] * exp (work[1*NSTEP+j] + work[2*NSTEP+j] * i + work[3*NSTEP+j] * ani + c); s[i] = scor * H; d += log ((double)(i + 1.0) / ani); } return; } void init (double work[]) { double xstart = -9.0, pi2 = -0.918938533, xx, alnorm(); int i; xx = xstart; /* set up arrays for calculation of integral */ for (i = 0; i < NSTEP; ++i) { work[0*NSTEP+i] = xx; work[1*NSTEP+i] = pi2 - xx * xx * 0.5; work[2*NSTEP+i] = log (alnorm (xx,1)); work[3*NSTEP+i] = log (alnorm (xx,0)); xx = xstart + H * (i + 1.0); } return; } double alnfac (int j) /*-Algorithm AS 177.2 Appl. Statist. (1982) Vol.31, No.2 * Natural logarithm of factorial for non-negative argument */ { static double r[7] = {0.0, 0.0, 0.69314718056, 1.79175946923, 3.17805383035, 4.78749174278, 6.57925121101}; double w, z; if (j == 1) return (double) 1.0; else if (j <= 7) return r[j]; w = (double) j + 1; z = 1.0 / (w * w); return (w - 0.5) * log (w) - w + 0.918938522305 + (((4.0 - 3.0 * z) * z - 14.0) * z + 420.0) / (5040.0 * w); } void nscor2 (double s[], int n, int n2, int *ifault) /*-Algorithm AS 177.3 Appl. Statist. (1982) Vol.31, No.2 * Approximation for Rankits */ { static double eps[4] = {0.419885, 0.450536, 0.456936, 0.468488}; static double dl1[4] = {0.112063, 0.121770, 0.239299, 0.215159}; static double dl2[4] = {0.080122, 0.111348, -0.211867, -0.115049}; static double gam[4] = {0.474798, 0.469051, 0.208597, 0.259784}; static double lam[4] = {0.282765, 0.304856, 0.407708, 0.414093}; static double bb = -0.283833, d = -0.106136, b1 = 0.5641896; double e1, e2, l1, correc(), ppnd16(); int i, k; *ifault = 3; if (n2 != n / 2) return; *ifault = 1; if (n <= 1) return; *ifault = 0; if (n > 2000) *ifault = 2; s[0] = b1; if (n == 2) return; /* calculate normal areas for 3 largest rankits */ k=(n2<3) ? n2 : 3; for (i = 0; i < k; ++i) { e1 = (1.0 + i - eps[i]) / (n + gam[i]); e2 = pow (e1, lam[i]); s[i] = e1 + e2 * (dl1[i] + e2 * dl2[i]) / n - correc (1 + i, n); } if (n2 != k) { /* calculate normal areas for remaining rankits */ for (i = 3; i < n2; ++i) { l1 = lam[3] + bb / (1.0 + i + d); e1 = (1.0 + i - eps[3]) / (n + gam[3]); e2 = pow (e1, l1); s[i] = e1 + e2 * (dl1[3] + e2 * dl2[3]) / n - correc (1+i, n); } } /* convert normal tail areas to normal deviates */ for (i = 0; i < n2; ++i) s[i] = -ppnd16 (s[i]); return; } double correc (int i, int n) /*-Algorithm AS 177.4 Appl. Statist. (1982) Vol.31, No.2 * Calculates correction for tail area of noraml distribution * corresponding to ith largest rankit in sample size n. */ { static double c1[7] = {9.5, 28.7, 1.9, 0.0, -7.0, -6.2, -1.6}; static double c2[7] = {-6.195e3, -9.569e3, -6.728e3, -17.614e3, -8.278e3, -3.570e3, 1.075e3}; static double c3[7] = {9.338e4, 1.7516e5, 4.1040e5, 2.157e6, 2.376e6, 2.065e6, 2.065e6}; static double mic = 1.0e-6, c14 = 1.9e-5; double an, ret_val; ret_val = c14; if (i * n == 4) return ret_val; ret_val = 0.0; if (i < 1 || i > 7) return ret_val; else if (i != 4 && n > 20) return ret_val; else if (i == 4 && n > 40) return ret_val; else { an = 1.0 / (double) (n * n); ret_val = (c1[i-1] + an * (c2[i-1] + an * c3[i-1])) * mic; return ret_val; } }