double lchoose(double n, double k)
{
double k0 = k;
k = floor(k + 0.5);
#ifdef IEEE_754
/* NaNs propagated correctly */
if(ISNAN(n) || ISNAN(k)) return n + k;
#endif
if (fabs(k - k0) > 1e-7)
MATHLIB_WARNING2(_("'k' (%.2f) must be integer, rounded to %.0f"), k0, k);
if (k < 2) {
if (k < 0) return ML_NEGINF;
if (k == 0) return 0.;
/* else: k == 1 */
return log(fabs(n));
}
/* else: k >= 2 */
if (n < 0) {
return lchoose(-n+ k-1, k);
}
else if (R_IS_INT(n)) {
if(n < k) return ML_NEGINF;
/* k <= n :*/
if(n - k < 2) return lchoose(n, n-k); /* <- Symmetry */
/* else: n >= k+2 */
return lfastchoose(n, k);
}
/* else non-integer n >= 0 : */
if (n < k-1) {
int s;
return lfastchoose2(n, k, &s);
}
return lfastchoose(n, k);
}
double psigamma(double x, double deriv)
{
/* n-th derivative of psi(x); e.g., psigamma(x,0) == digamma(x) */
double ans;
int nz, ierr, k, n;
if(ISNAN(x))
return x;
deriv = floor(deriv + 0.5);
n = (int)deriv;
if(n > n_max) {
MATHLIB_WARNING2(_("deriv = %d > %d (= n_max)"), n, n_max);
return ML_NAN;
}
dpsifn(x, n, 1, 1, &ans, &nz, &ierr);
if(ierr != 0) {
errno = EDOM;
return ML_NAN;
}
/* ans == A := (-1)^(n+1) / gamma(n+1) * psi(n, x) */
ans = -ans; /* = (-1)^(0+1) * gamma(0+1) * A */
for(k = 1; k <= n; k++)
ans *= (-k);/* = (-1)^(k+1) * gamma(k+1) * A */
return ans;/* = psi(n, x) */
}
/* modified version of bessel_k that accepts a work array instead of
allocating one. */
double bessel_k_ex(double x, double alpha, double expo, double *bk)
{
long nb, ncalc, ize;
#ifdef IEEE_754
/* NaNs propagated correctly */
if (ISNAN(x) || ISNAN(alpha)) return x + alpha;
#endif
if (x < 0) {
ML_ERROR(ME_RANGE, "bessel_k");
return ML_NAN;
}
ize = (long)expo;
if(alpha < 0)
alpha = -alpha;
nb = 1+ (long)floor(alpha);/* nb-1 <= |alpha| < nb */
alpha -= (double)(nb-1);
K_bessel(&x, &alpha, &nb, &ize, bk, &ncalc);
if(ncalc != nb) {/* error input */
if(ncalc < 0)
MATHLIB_WARNING4(_("bessel_k(%g): ncalc (=%ld) != nb (=%ld); alpha=%g. Arg. out of range?\n"),
x, ncalc, nb, alpha);
else
MATHLIB_WARNING2(_("bessel_k(%g,nu=%g): precision lost in result\n"),
x, alpha+(double)nb-1);
}
x = bk[nb-1];
return x;
}
/* modified version of bessel_j that accepts a work array instead of
allocating one. */
double bessel_j_ex(double x, double alpha, double *bj)
{
long nb, ncalc;
double na;
#ifdef IEEE_754
/* NaNs propagated correctly */
if (ISNAN(x) || ISNAN(alpha)) return x + alpha;
#endif
if (x < 0) {
ML_ERROR(ME_RANGE, "bessel_j");
return ML_NAN;
}
na = floor(alpha);
if (alpha < 0) {
/* Using Abramowitz & Stegun 9.1.2
* this may not be quite optimal (CPU and accuracy wise) */
return(bessel_j_ex(x, -alpha, bj) * cos(M_PI * alpha) +
((alpha == na) ? 0 :
bessel_y_ex(x, -alpha, bj) * sin(M_PI * alpha)));
}
nb = 1 + (long)na; /* nb-1 <= alpha < nb */
alpha -= (nb-1);
J_bessel(&x, &alpha, &nb, bj, &ncalc);
if(ncalc != nb) {/* error input */
if(ncalc < 0)
MATHLIB_WARNING4(_("bessel_j(%g): ncalc (=%ld) != nb (=%ld); alpha=%g. Arg. out of range?\n"),
x, ncalc, nb, alpha);
else
MATHLIB_WARNING2(_("bessel_j(%g,nu=%g): precision lost in result\n"),
x, alpha+nb-1);
}
x = bj[nb-1];
return x;
}
// unused now from R
double bessel_j(double x, double alpha)
{
int nb, ncalc;
double na, *bj;
#ifndef MATHLIB_STANDALONE
const void *vmax;
#endif
#ifdef IEEE_754
/* NaNs propagated correctly */
if (ISNAN(x) || ISNAN(alpha)) return x + alpha;
#endif
if (x < 0) {
ML_ERROR(ME_RANGE, "bessel_j");
return ML_NAN;
}
na = floor(alpha);
if (alpha < 0) {
/* Using Abramowitz & Stegun 9.1.2
* this may not be quite optimal (CPU and accuracy wise) */
return(((alpha - na == 0.5) ? 0 : bessel_j(x, -alpha) * cospi(alpha)) +
((alpha == na ) ? 0 : bessel_y(x, -alpha) * sinpi(alpha)));
}
else if (alpha > 1e7) {
MATHLIB_WARNING("besselJ(x, nu): nu=%g too large for bessel_j() algorithm", alpha);
return ML_NAN;
}
nb = 1 + (int)na; /* nb-1 <= alpha < nb */
alpha -= (double)(nb-1);
#ifdef MATHLIB_STANDALONE
bj = (double *) calloc(nb, sizeof(double));
#ifndef _RENJIN
if (!bj) MATHLIB_ERROR("%s", _("bessel_j allocation error"));
#endif
#else
vmax = vmaxget();
bj = (double *) R_alloc((size_t) nb, sizeof(double));
#endif
J_bessel(&x, &alpha, &nb, bj, &ncalc);
if(ncalc != nb) {/* error input */
if(ncalc < 0)
MATHLIB_WARNING4(_("bessel_j(%g): ncalc (=%d) != nb (=%d); alpha=%g. Arg. out of range?\n"),
x, ncalc, nb, alpha);
else
MATHLIB_WARNING2(_("bessel_j(%g,nu=%g): precision lost in result\n"),
x, alpha+(double)nb-1);
}
x = bj[nb-1];
#ifdef MATHLIB_STANDALONE
free(bj);
#else
vmaxset(vmax);
#endif
return x;
}
double bessel_y(double x, double alpha)
{
long nb, ncalc;
double na, *by;
#ifndef MATHLIB_STANDALONE
const void *vmax;
#endif
#ifdef IEEE_754
/* NaNs propagated correctly */
if (ISNAN(x) || ISNAN(alpha)) return x + alpha;
#endif
if (x < 0) {
ML_ERROR(ME_RANGE, "bessel_y");
return ML_NAN;
}
na = floor(alpha);
if (alpha < 0) {
/* Using Abramowitz & Stegun 9.1.2
* this may not be quite optimal (CPU and accuracy wise) */
return(bessel_y(x, -alpha) * cos(M_PI * alpha) -
((alpha == na) ? 0 :
bessel_j(x, -alpha) * sin(M_PI * alpha)));
}
nb = 1+ (long)na;/* nb-1 <= alpha < nb */
alpha -= (nb-1);
#ifdef MATHLIB_STANDALONE
by = (double *) calloc(nb, sizeof(double));
if (!by) MATHLIB_ERROR("%s", _("bessel_y allocation error"));
#else
vmax = vmaxget();
by = (double *) R_alloc((size_t) nb, sizeof(double));
#endif
Y_bessel(&x, &alpha, &nb, by, &ncalc);
if(ncalc != nb) {/* error input */
if(ncalc == -1)
return ML_POSINF;
else if(ncalc < -1)
MATHLIB_WARNING4(_("bessel_y(%g): ncalc (=%ld) != nb (=%ld); alpha=%g. Arg. out of range?\n"),
x, ncalc, nb, alpha);
else /* ncalc >= 0 */
MATHLIB_WARNING2(_("bessel_y(%g,nu=%g): precision lost in result\n"),
x, alpha+nb-1);
}
x = by[nb-1];
#ifdef MATHLIB_STANDALONE
free(by);
#else
vmaxset(vmax);
#endif
return x;
}
double bessel_k(double x, double alpha, double expo)
{
long nb, ncalc, ize;
double *bk;
#ifndef MATHLIB_STANDALONE
const void *vmax;
#endif
#ifdef IEEE_754
/* NaNs propagated correctly */
if (ISNAN(x) || ISNAN(alpha)) return x + alpha;
#endif
if (x < 0) {
ML_ERROR(ME_RANGE, "bessel_k");
return ML_NAN;
}
ize = (long)expo;
if(alpha < 0)
alpha = -alpha;
nb = 1+ (long)floor(alpha);/* nb-1 <= |alpha| < nb */
alpha -= (double)(nb-1);
#ifdef MATHLIB_STANDALONE
bk = (double *) calloc(nb, sizeof(double));
if (!bk) MATHLIB_ERROR("%s", _("bessel_k allocation error"));
#else
vmax = vmaxget();
bk = (double *) R_alloc((size_t) nb, sizeof(double));
#endif
K_bessel(&x, &alpha, &nb, &ize, bk, &ncalc);
if(ncalc != nb) {/* error input */
if(ncalc < 0)
MATHLIB_WARNING4(_("bessel_k(%g): ncalc (=%ld) != nb (=%ld); alpha=%g. Arg. out of range?\n"),
x, ncalc, nb, alpha);
else
MATHLIB_WARNING2(_("bessel_k(%g,nu=%g): precision lost in result\n"),
x, alpha+(double)nb-1);
}
x = bk[nb-1];
#ifdef MATHLIB_STANDALONE
free(bk);
#else
vmaxset(vmax);
#endif
return x;
}
/* 30 is somewhat arbitrary: it is on the *safe* side:
* both speed and precision are clearly improved for k < 30.
*/
double choose(double n, double k)
{
double r, k0 = k;
k = R_forceint(k);
#ifdef IEEE_754
/* NaNs propagated correctly */
if(ISNAN(n) || ISNAN(k)) return n + k;
#endif
#ifndef MATHLIB_STANDALONE
R_CheckStack();
#endif
if (fabs(k - k0) > 1e-7)
MATHLIB_WARNING2(_("'k' (%.2f) must be integer, rounded to %.0f"), k0, k);
if (k < k_small_max) {
int j;
if(n-k < k && n >= 0 && R_IS_INT(n)) k = n-k; /* <- Symmetry */
if (k < 0) return 0.;
if (k == 0) return 1.;
/* else: k >= 1 */
r = n;
for(j = 2; j <= k; j++)
r *= (n-j+1)/j;
return R_IS_INT(n) ? R_forceint(r) : r;
/* might have got rounding errors */
}
/* else: k >= k_small_max */
if (n < 0) {
r = choose(-n+ k-1, k);
if (ODD(k)) r = -r;
return r;
}
else if (R_IS_INT(n)) {
n = R_forceint(n);
if(n < k) return 0.;
if(n - k < k_small_max) return choose(n, n-k); /* <- Symmetry */
return R_forceint(exp(lfastchoose(n, k)));
}
/* else non-integer n >= 0 : */
if (n < k-1) {
int s_choose;
r = lfastchoose2(n, k, /* -> */ &s_choose);
return s_choose * exp(r);
}
return exp(lfastchoose(n, k));
}
/* Called from R: modified version of bessel_j(), accepting a work array
* instead of allocating one. */
double bessel_j_ex(double x, double alpha, double *bj)
{
int nb, ncalc;
double na;
#ifdef IEEE_754
/* NaNs propagated correctly */
if (ISNAN(x) || ISNAN(alpha)) return x + alpha;
#endif
if (x < 0) {
ML_ERROR(ME_RANGE, "bessel_j");
return ML_NAN;
}
na = floor(alpha);
if (alpha < 0) {
/* Using Abramowitz & Stegun 9.1.2
* this may not be quite optimal (CPU and accuracy wise) */
return(((alpha - na == 0.5) ? 0 : bessel_j_ex(x, -alpha, bj) * cospi(alpha)) +
((alpha == na ) ? 0 : bessel_y_ex(x, -alpha, bj) * sinpi(alpha)));
}
else if (alpha > 1e7) {
MATHLIB_WARNING("besselJ(x, nu): nu=%g too large for bessel_j() algorithm", alpha);
return ML_NAN;
}
nb = 1 + (int)na; /* nb-1 <= alpha < nb */
alpha -= (double)(nb-1); // ==> alpha' in [0, 1)
J_bessel(&x, &alpha, &nb, bj, &ncalc);
if(ncalc != nb) {/* error input */
if(ncalc < 0)
MATHLIB_WARNING4(_("bessel_j(%g): ncalc (=%d) != nb (=%d); alpha=%g. Arg. out of range?\n"),
x, ncalc, nb, alpha);
else
MATHLIB_WARNING2(_("bessel_j(%g,nu=%g): precision lost in result\n"),
x, alpha+(double)nb-1);
}
x = bj[nb-1];
return x;
}
double attribute_hidden
pnchisq_raw(double x, double f, double theta,
double errmax, double reltol, int itrmax, Rboolean lower_tail)
{
double lam, x2, f2, term, bound, f_x_2n, f_2n;
double l_lam = -1., l_x = -1.; /* initialized for -Wall */
int n;
Rboolean lamSml, tSml, is_r, is_b, is_it;
LDOUBLE ans, u, v, t, lt, lu =-1;
static const double _dbl_min_exp = M_LN2 * DBL_MIN_EXP;
/*= -708.3964 for IEEE double precision */
if (x <= 0.) {
if(x == 0. && f == 0.)
return lower_tail ? exp(-0.5*theta) : -expm1(-0.5*theta);
/* x < 0 or {x==0, f > 0} */
return lower_tail ? 0. : 1.;
}
if(!R_FINITE(x)) return lower_tail ? 1. : 0.;
/* This is principally for use from qnchisq */
#ifndef MATHLIB_STANDALONE
R_CheckUserInterrupt();
#endif
if(theta < 80) { /* use 110 for Inf, as ppois(110, 80/2, lower.tail=FALSE) is 2e-20 */
LDOUBLE sum = 0, sum2 = 0, lambda = 0.5*theta,
pr = EXP(-lambda); // does this need a feature test?
double ans;
int i;
/* we need to renormalize here: the result could be very close to 1 */
for(i = 0; i < 110; pr *= lambda/++i) {
sum2 += pr;
sum += pr * pchisq(x, f+2*i, lower_tail, FALSE);
if (sum2 >= 1-1e-15) break;
}
ans = (double) (sum/sum2);
return ans;
}
#ifdef DEBUG_pnch
REprintf("pnchisq(x=%g, f=%g, theta=%g): ",x,f,theta);
#endif
lam = .5 * theta;
lamSml = (-lam < _dbl_min_exp);
if(lamSml) {
/* MATHLIB_ERROR(
"non centrality parameter (= %g) too large for current algorithm",
theta) */
u = 0;
lu = -lam;/* == ln(u) */
l_lam = log(lam);
} else {
u = exp(-lam);
}
/* evaluate the first term */
v = u;
x2 = .5 * x;
f2 = .5 * f;
f_x_2n = f - x;
#ifdef DEBUG_pnch
REprintf("-- v=exp(-th/2)=%g, x/2= %g, f/2= %g\n",v,x2,f2);
#endif
if(f2 * DBL_EPSILON > 0.125 && /* very large f and x ~= f: probably needs */
FABS(t = x2 - f2) < /* another algorithm anyway */
sqrt(DBL_EPSILON) * f2) {
/* evade cancellation error */
/* t = exp((1 - t)*(2 - t/(f2 + 1))) / sqrt(2*M_PI*(f2 + 1));*/
lt = (1 - t)*(2 - t/(f2 + 1)) - 0.5 * log(2*M_PI*(f2 + 1));
#ifdef DEBUG_pnch
REprintf(" (case I) ==> ");
#endif
}
else {
/* Usual case 2: careful not to overflow .. : */
lt = f2*log(x2) -x2 - lgammafn(f2 + 1);
}
#ifdef DEBUG_pnch
REprintf(" lt= %g", lt);
#endif
tSml = (lt < _dbl_min_exp);
if(tSml) {
if (x > f + theta + 5* sqrt( 2*(f + 2*theta))) {
/* x > E[X] + 5* sigma(X) */
return lower_tail ? 1. : 0.; /* FIXME: We could be more accurate than 0. */
} /* else */
l_x = log(x);
ans = term = 0.; t = 0;
}
else {
t = EXP(lt);
#ifdef DEBUG_pnch
REprintf(", t=exp(lt)= %g\n", t);
#endif
ans = term = (double) (v * t);
}
for (n = 1, f_2n = f + 2., f_x_2n += 2.; ; n++, f_2n += 2, f_x_2n += 2) {
#ifdef DEBUG_pnch
REprintf("\n _OL_: n=%d",n);
#endif
#ifndef MATHLIB_STANDALONE
if(n % 1000) R_CheckUserInterrupt();
#endif
/* f_2n === f + 2*n
* f_x_2n === f - x + 2*n > 0 <==> (f+2n) > x */
if (f_x_2n > 0) {
/* find the error bound and check for convergence */
bound = (double) (t * x / f_x_2n);
#ifdef DEBUG_pnch
REprintf("\n L10: n=%d; term= %g; bound= %g",n,term,bound);
#endif
is_r = is_it = FALSE;
/* convergence only if BOTH absolute and relative error < 'bnd' */
if (((is_b = (bound <= errmax)) &&
(is_r = (term <= reltol * ans))) || (is_it = (n > itrmax)))
{
#ifdef DEBUG_pnch
REprintf("BREAK n=%d %s; bound= %g %s, rel.err= %g %s\n",
n, (is_it ? "> itrmax" : ""),
bound, (is_b ? "<= errmax" : ""),
term/ans, (is_r ? "<= reltol" : ""));
#endif
break; /* out completely */
}
}
/* evaluate the next term of the */
/* expansion and then the partial sum */
if(lamSml) {
lu += l_lam - log(n); /* u = u* lam / n */
if(lu >= _dbl_min_exp) {
/* no underflow anymore ==> change regime */
#ifdef DEBUG_pnch
REprintf(" n=%d; nomore underflow in u = exp(lu) ==> change\n",
n);
#endif
v = u = EXP(lu); /* the first non-0 'u' */
lamSml = FALSE;
}
} else {
u *= lam / n;
v += u;
}
if(tSml) {
lt += l_x - log(f_2n);/* t <- t * (x / f2n) */
if(lt >= _dbl_min_exp) {
/* no underflow anymore ==> change regime */
#ifdef DEBUG_pnch
REprintf(" n=%d; nomore underflow in t = exp(lt) ==> change\n",
n);
#endif
t = EXP(lt); /* the first non-0 't' */
tSml = FALSE;
}
} else {
t *= x / f_2n;
}
if(!lamSml && !tSml) {
term = (double) (v * t);
ans += term;
}
} /* for(n ...) */
if (is_it) {
MATHLIB_WARNING2(_("pnchisq(x=%g, ..): not converged in %d iter."),
x, itrmax);
}
#ifdef DEBUG_pnch
REprintf("\n == L_End: n=%d; term= %g; bound=%g\n",n,term,bound);
#endif
return (double) (lower_tail ? ans : 1 - ans);
}
double pnchisq_raw(double x, double f, double theta,
double errmax, double reltol, int itrmax)
{
double ans, lam, u, v, x2, f2, t, term, bound, f_x_2n, f_2n, lt;
double lu = -1., l_lam = -1., l_x = -1.; /* initialized for -Wall */
int n;
Rboolean lamSml, tSml, is_r, is_b, is_it;
static const double _dbl_min_exp = M_LN2 * DBL_MIN_EXP;
/*= -708.3964 for IEEE double precision */
if (x <= 0.) return 0.;
if(!R_FINITE(x)) return 1.;
#ifdef DEBUG_pnch
REprintf("pnchisq(x=%g, f=%g, theta=%g): ",x,f,theta);
#endif
lam = .5 * theta;
lamSml = (-lam < _dbl_min_exp);
if(lamSml) {
/* MATHLIB_ERROR(
"non centrality parameter (= %g) too large for current algorithm",
theta) */
u = 0;
lu = -lam;/* == ln(u) */
l_lam = log(lam);
} else {
u = exp(-lam);
}
/* evaluate the first term */
v = u;
x2 = .5 * x;
f2 = .5 * f;
f_x_2n = f - x;
#ifdef DEBUG_pnch
REprintf("-- v=exp(-th/2)=%g, x/2= %g, f/2= %g\n",v,x2,f2);
#endif
if(f2 * DBL_EPSILON > 0.125 && /* very large f and x ~= f: probably needs */
fabs(t = x2 - f2) < /* other algorithm anyway */
sqrt(DBL_EPSILON) * f2) {
/* evade cancellation error */
/* t = exp((1 - t)*(2 - t/(f2 + 1))) / sqrt(2*M_PI*(f2 + 1));*/
lt = (1 - t)*(2 - t/(f2 + 1)) - 0.5 * log(2*M_PI*(f2 + 1));
#ifdef DEBUG_pnch
REprintf(" (case I) ==> ");
#endif
}
else {
/* Usual case 2: careful not to overflow .. : */
lt = f2*log(x2) -x2 - lgammafn(f2 + 1);
}
#ifdef DEBUG_pnch
REprintf(" lt= %g", lt);
#endif
tSml = (lt < _dbl_min_exp);
if(tSml) {
if (x > f + theta + 5* sqrt( 2*(f + 2*theta))) {
/* x > E[X] + 5* sigma(X) */
return 1.; /* better than 0 --- but definitely "FIXME" */
} /* else */
l_x = log(x);
ans = term = t = 0.;
}
else {
t = exp(lt);
#ifdef DEBUG_pnch
REprintf(", t=exp(lt)= %g\n", t);
#endif
ans = term = v * t;
}
for (n = 1, f_2n = f + 2., f_x_2n += 2.; ; n++, f_2n += 2, f_x_2n += 2) {
#ifdef DEBUG_pnch
REprintf("\n _OL_: n=%d",n);
#endif
/* f_2n === f + 2*n
* f_x_2n === f - x + 2*n > 0 <==> (f+2n) > x */
if (f_x_2n > 0) {
/* find the error bound and check for convergence */
bound = t * x / f_x_2n;
#ifdef DEBUG_pnch
REprintf("\n L10: n=%d; term= %g; bound= %g",n,term,bound);
#endif
is_r = is_it = FALSE;
/* convergence only if BOTH absolute and relative error < 'bnd' */
if (((is_b = (bound <= errmax)) &&
(is_r = (term <= reltol * ans))) || (is_it = (n > itrmax)))
{
#ifdef DEBUG_pnch
REprintf("BREAK n=%d %s; bound= %g %s, rel.err= %g %s\n",
n, (is_it ? "> itrmax" : ""),
bound, (is_b ? "<= errmax" : ""),
term/ans, (is_r ? "<= reltol" : ""));
#endif
break; /* out completely */
}
}
/* evaluate the next term of the */
/* expansion and then the partial sum */
if(lamSml) {
lu += l_lam - log(n); /* u = u* lam / n */
if(lu >= _dbl_min_exp) {
/* no underflow anymore ==> change regime */
#ifdef DEBUG_pnch
REprintf(" n=%d; nomore underflow in u = exp(lu) ==> change\n",
n);
#endif
v = u = exp(lu); /* the first non-0 'u' */
lamSml = FALSE;
}
} else {
u *= lam / n;
v += u;
}
if(tSml) {
lt += l_x - log(f_2n);/* t <- t * (x / f2n) */
if(lt >= _dbl_min_exp) {
/* no underflow anymore ==> change regime */
#ifdef DEBUG_pnch
REprintf(" n=%d; nomore underflow in t = exp(lt) ==> change\n",
n);
#endif
t = exp(lt); /* the first non-0 't' */
tSml = FALSE;
}
} else {
t *= x / f_2n;
}
if(!lamSml && !tSml) {
term = v * t;
ans += term;
}
} /* for(n ...) */
if (is_it) {
MATHLIB_WARNING2(_("pnchisq(x=%g, ..): not converged in %d iter."),
x, itrmax);
}
#ifdef DEBUG_pnch
REprintf("\n == L_End: n=%d; term= %g; bound=%g\n",n,term,bound);
#endif
return (ans);
}
// Returns both qbeta() and its "mirror" 1-qbeta(). Useful notably when qbeta() ~= 1
attribute_hidden void
qbeta_raw(double alpha, double p, double q, int lower_tail, int log_p,
int swap_01, // {TRUE, NA, FALSE}: if NA, algorithm decides swap_tail
double log_q_cut, /* if == Inf: return log(qbeta(..));
otherwise, if finite: the bound for
switching to log(x)-scale; see use_log_x */
int n_N, // number of "unconstrained" Newton steps before switching to constrained
double *qb) // = qb[0:1] = { qbeta(), 1 - qbeta() }
{
Rboolean
swap_choose = (swap_01 == MLOGICAL_NA),
swap_tail,
log_, give_log_q = (log_q_cut == ML_POSINF),
use_log_x = give_log_q, // or u < log_q_cut below
warned = FALSE, add_N_step = TRUE;
int i_pb, i_inn;
double a, la, logbeta, g, h, pp, p_, qq, r, s, t, w, y = -1.;
volatile double u, xinbta;
// Assuming p >= 0, q >= 0 here ...
// Deal with boundary cases here:
if(alpha == R_DT_0) {
#define return_q_0 \
if(give_log_q) { qb[0] = ML_NEGINF; qb[1] = 0; } \
else { qb[0] = 0; qb[1] = 1; } \
return
return_q_0;
}
if(alpha == R_DT_1) {
#define return_q_1 \
if(give_log_q) { qb[0] = 0; qb[1] = ML_NEGINF; } \
else { qb[0] = 1; qb[1] = 0; } \
return
return_q_1;
}
// check alpha {*before* transformation which may all accuracy}:
if((log_p && alpha > 0) ||
(!log_p && (alpha < 0 || alpha > 1))) { // alpha is outside
R_ifDEBUG_printf("qbeta(alpha=%g, %g, %g, .., log_p=%d): %s%s\n",
alpha, p,q, log_p, "alpha not in ",
log_p ? "[-Inf, 0]" : "[0,1]");
// ML_ERR_return_NAN :
ML_ERROR(ME_DOMAIN, "");
qb[0] = qb[1] = ML_NAN; return;
}
// p==0, q==0, p = Inf, q = Inf <==> treat as one- or two-point mass
if(p == 0 || q == 0 || !R_FINITE(p) || !R_FINITE(q)) {
// We know 0 < T(alpha) < 1 : pbeta() is constant and trivial in {0, 1/2, 1}
R_ifDEBUG_printf(
"qbeta(%g, %g, %g, lower_t=%d, log_p=%d): (p,q)-boundary: trivial\n",
alpha, p,q, lower_tail, log_p);
if(p == 0 && q == 0) { // point mass 1/2 at each of {0,1} :
if(alpha < R_D_half) { return_q_0; }
if(alpha > R_D_half) { return_q_1; }
// else: alpha == "1/2"
#define return_q_half \
if(give_log_q) qb[0] = qb[1] = -M_LN2; \
else qb[0] = qb[1] = 0.5; \
return
return_q_half;
} else if (p == 0 || p/q == 0) { // point mass 1 at 0 - "flipped around"
return_q_0;
} else if (q == 0 || q/p == 0) { // point mass 1 at 0 - "flipped around"
return_q_1;
}
// else: p = q = Inf : point mass 1 at 1/2
return_q_half;
}
/* initialize */
p_ = R_DT_qIv(alpha);/* lower_tail prob (in any case) */
// Conceptually, 0 < p_ < 1 (but can be 0 or 1 because of cancellation!)
logbeta = lbeta(p, q);
swap_tail = (swap_choose) ? (p_ > 0.5) : swap_01;
// change tail; default (swap_01 = NA): afterwards 0 < a <= 1/2
if(swap_tail) { /* change tail, swap p <-> q :*/
a = R_DT_CIv(alpha); // = 1 - p_ < 1/2
/* la := log(a), but without numerical cancellation: */
la = R_DT_Clog(alpha);
pp = q; qq = p;
}
else {
a = p_;
la = R_DT_log(alpha);
pp = p; qq = q;
}
/* calculate the initial approximation */
/* Desired accuracy for Newton iterations (below) should depend on (a,p)
* This is from Remark .. on AS 109, adapted.
* However, it's not clear if this is "optimal" for IEEE double prec.
* acu = fmax2(acu_min, pow(10., -25. - 5./(pp * pp) - 1./(a * a)));
* NEW: 'acu' accuracy NOT for squared adjustment, but simple;
* ---- i.e., "new acu" = sqrt(old acu)
*/
double acu = fmax2(acu_min, pow(10., -13. - 2.5/(pp * pp) - 0.5/(a * a)));
// try to catch "extreme left tail" early
double tx, u0 = (la + log(pp) + logbeta) / pp; // = log(x_0)
static const double
log_eps_c = M_LN2 * (1. - DBL_MANT_DIG);// = log(DBL_EPSILON) = -36.04..
r = pp*(1.-qq)/(pp+1.);
t = 0.2;
// FIXME: Factor 0.2 is a bit arbitrary; '1' is clearly much too much.
R_ifDEBUG_printf(
"qbeta(%g, %g, %g, lower_t=%d, log_p=%d):%s\n"
" swap_tail=%d, la=%g, u0=%g (bnd: %g (%g)) ",
alpha, p,q, lower_tail, log_p,
(log_p && (p_ == 0. || p_ == 1.)) ? (p_==0.?" p_=0":" p_=1") : "",
swap_tail, la, u0,
(t*log_eps_c - log(fabs(pp*(1.-qq)*(2.-qq)/(2.*(pp+2.)))))/2.,
t*log_eps_c - log(fabs(r))
);
if(M_LN2 * DBL_MIN_EXP < u0 && // cannot allow exp(u0) = 0 ==> exp(u1) = exp(u0) = 0
u0 < -0.01 && // (must: u0 < 0, but too close to 0 <==> x = exp(u0) = 0.99..)
// qq <= 2 && // <--- "arbitrary"
// u0 < t*log_eps_c - log(fabs(r)) &&
u0 < (t*log_eps_c - log(fabs(pp*(1.-qq)*(2.-qq)/(2.*(pp+2.)))))/2.)
{
// TODO: maybe jump here from below, when initial u "fails" ?
// L_tail_u:
// MM's one-step correction (cheaper than 1 Newton!)
r = r*exp(u0);// = r*x0
if(r > -1.) {
u = u0 - log1p(r)/pp;
R_ifDEBUG_printf("u1-u0=%9.3g --> choosing u = u1\n", u-u0);
} else {
u = u0;
R_ifDEBUG_printf("cannot cheaply improve u0\n");
}
tx = xinbta = exp(u);
use_log_x = TRUE; // or (u < log_q_cut) ??
goto L_Newton;
}
// y := y_\alpha in AS 64 := Hastings(1955) approximation of qnorm(1 - a) :
r = sqrt(-2 * la);
y = r - (const1 + const2 * r) / (1. + (const3 + const4 * r) * r);
if (pp > 1 && qq > 1) { // use Carter(1947), see AS 109, remark '5.'
r = (y * y - 3.) / 6.;
s = 1. / (pp + pp - 1.);
t = 1. / (qq + qq - 1.);
h = 2. / (s + t);
w = y * sqrt(h + r) / h - (t - s) * (r + 5. / 6. - 2. / (3. * h));
R_ifDEBUG_printf("p,q > 1 => w=%g", w);
if(w > 300) { // exp(w+w) is huge or overflows
t = w+w + log(qq) - log(pp); // = argument of log1pexp(.)
u = // log(xinbta) = - log1p(qq/pp * exp(w+w)) = -log(1 + exp(t))
(t <= 18) ? -log1p(exp(t)) : -t - exp(-t);
xinbta = exp(u);
} else {
xinbta = pp / (pp + qq * exp(w + w));
u = // log(xinbta)
- log1p(qq/pp * exp(w+w));
}
} else { // use the original AS 64 proposal, Scheffé-Tukey (1944) and Wilson-Hilferty
r = qq + qq;
/* A slightly more stable version of t := \chi^2_{alpha} of AS 64
* t = 1. / (9. * qq); t = r * R_pow_di(1. - t + y * sqrt(t), 3); */
t = 1. / (3. * sqrt(qq));
t = r * R_pow_di(1. + t*(-t + y), 3);// = \chi^2_{alpha} of AS 64
s = 4. * pp + r - 2.;// 4p + 2q - 2 = numerator of new t = (...) / chi^2
R_ifDEBUG_printf("min(p,q) <= 1: t=%g", t);
if (t == 0 || (t < 0. && s >= t)) { // cannot use chisq approx
// x0 = 1 - { (1-a)*q*B(p,q) } ^{1/q} {AS 65}
// xinbta = 1. - exp((log(1-a)+ log(qq) + logbeta) / qq);
double l1ma;/* := log(1-a), directly from alpha (as 'la' above):
* FIXME: not worth it? log1p(-a) always the same ?? */
if(swap_tail)
l1ma = R_DT_log(alpha);
else
l1ma = R_DT_Clog(alpha);
R_ifDEBUG_printf(" t <= 0 : log1p(-a)=%.15g, better l1ma=%.15g\n", log1p(-a), l1ma);
double xx = (l1ma + log(qq) + logbeta) / qq;
if(xx <= 0.) {
xinbta = -expm1(xx);
u = R_Log1_Exp (xx);// = log(xinbta) = log(1 - exp(...A...))
} else { // xx > 0 ==> 1 - e^xx < 0 .. is nonsense
R_ifDEBUG_printf(" xx=%g > 0: xinbta:= 1-e^xx < 0\n", xx);
xinbta = 0; u = ML_NEGINF; /// FIXME can do better?
}
} else {
t = s / t;
R_ifDEBUG_printf(" t > 0 or s < t < 0: new t = %g ( > 1 ?)\n", t);
if (t <= 1.) { // cannot use chisq, either
u = (la + log(pp) + logbeta) / pp;
xinbta = exp(u);
} else { // (1+x0)/(1-x0) = t, solved for x0 :
xinbta = 1. - 2. / (t + 1.);
u = log1p(-2. / (t + 1.));
}
}
}
// Problem: If initial u is completely wrong, we make a wrong decision here
if(swap_choose &&
(( swap_tail && u >= -exp( log_q_cut)) || // ==> "swap back"
(!swap_tail && u >= -exp(4*log_q_cut) && pp / qq < 1000.))) { // ==> "swap now" (much less easily)
// "revert swap" -- and use_log_x
swap_tail = !swap_tail;
R_ifDEBUG_printf(" u = %g (e^u = xinbta = %.16g) ==> ", u, xinbta);
if(swap_tail) {
a = R_DT_CIv(alpha); // needed ?
la = R_DT_Clog(alpha);
pp = q; qq = p;
}
else {
a = p_;
la = R_DT_log(alpha);
pp = p; qq = q;
}
R_ifDEBUG_printf("\"%s\"; la = %g\n",
(swap_tail ? "swap now" : "swap back"), la);
// we could redo computations above, but this should be stable
u = R_Log1_Exp(u);
xinbta = exp(u);
/* Careful: "swap now" should not fail if
1) the above initial xinbta is "completely wrong"
2) The correction step can go outside (u_n > 0 ==> e^u > 1 is illegal)
e.g., for
qbeta(0.2066, 0.143891, 0.05)
*/
}
if(!use_log_x)
use_log_x = (u < log_q_cut);//(per default) <==> xinbta = e^u < 4.54e-5
Rboolean
bad_u = !R_FINITE(u),
bad_init = bad_u || xinbta > p_hi;
R_ifDEBUG_printf(" -> u = %g, e^u = xinbta = %.16g, (Newton acu=%g%s)\n",
u, xinbta, acu,
(bad_u ? ", ** bad u **" :
(use_log_x ? ", on u = log(x) scale" : "")));
double u_n = 1.; // -Wall
tx = xinbta; // keeping "original initial x" (for now)
if(bad_u || u < log_q_cut) { /* e.g.
qbeta(0.21, .001, 0.05)
try "left border" quickly, i.e.,
try at smallest positive number: */
w = pbeta_raw(DBL_very_MIN, pp, qq, TRUE, log_p);
if(w > (log_p ? la : a)) {
R_ifDEBUG_printf(" quantile is left of smallest positive number; \"convergence\"\n");
if(log_p || fabs(w - a) < fabs(0 - a)) { // DBL_very_MIN is better than 0
tx = DBL_very_MIN;
u_n = DBL_log_v_MIN;// = log(DBL_very_MIN)
} else {
tx = 0.;
u_n = ML_NEGINF;
}
use_log_x = log_p; add_N_step = FALSE; goto L_return;
}
else {
R_ifDEBUG_printf(" pbeta(smallest pos.) = %g <= %g --> continuing\n",
w, (log_p ? la : a));
if(u < DBL_log_v_MIN) {
u = DBL_log_v_MIN;// = log(DBL_very_MIN)
xinbta = DBL_very_MIN;
}
}
}
/* Sometimes the approximation is negative (and == 0 is also not "ok") */
if (bad_init && !(use_log_x && tx > 0)) {
if(u == ML_NEGINF) {
R_ifDEBUG_printf(" u = -Inf;");
u = M_LN2 * DBL_MIN_EXP;
xinbta = DBL_MIN;
} else {
R_ifDEBUG_printf(" bad_init: u=%g, xinbta=%g;", u,xinbta);
xinbta = (xinbta > 1.1) // i.e. "way off"
? 0.5 // otherwise, keep the respective boundary:
: ((xinbta < p_lo) ? exp(u) : p_hi);
if(bad_u)
u = log(xinbta);
// otherwise: not changing "potentially better" u than the above
}
R_ifDEBUG_printf(" -> (partly)new u=%g, xinbta=%g\n", u,xinbta);
}
L_Newton:
/* --------------------------------------------------------------------
* Solve for x by a modified Newton-Raphson method, using pbeta_raw()
*/
r = 1 - pp;
t = 1 - qq;
double wprev = 0., prev = 1., adj = 1.; // -Wall
if(use_log_x) { // find log(xinbta) -- work in u := log(x) scale
// if(bad_init && tx > 0) xinbta = tx;// may have been better
for (i_pb=0; i_pb < 1000; i_pb++) {
// using log_p == TRUE unconditionally here
// FIXME: if exp(u) = xinbta underflows to 0, like different formula pbeta_log(u, *)
y = pbeta_raw(xinbta, pp, qq, /*lower_tail = */ TRUE, TRUE);
/* w := Newton step size for L(u) = log F(e^u) =!= 0; u := log(x)
* = (L(.) - la) / L'(.); L'(u)= (F'(e^u) * e^u ) / F(e^u)
* = (L(.) - la)*F(.) / {F'(e^u) * e^u } =
* = (L(.) - la) * e^L(.) * e^{-log F'(e^u) - u}
* = ( y - la) * e^{ y - u -log F'(e^u)}
and -log F'(x)= -log f(x) = + logbeta + (1-p) log(x) + (1-q) log(1-x)
= logbeta + (1-p) u + (1-q) log(1-e^u)
*/
w = (y == ML_NEGINF) // y = -Inf well possible: we are on log scale!
? 0. : (y - la) * exp(y - u + logbeta + r * u + t * R_Log1_Exp(u));
if(!R_FINITE(w))
break;
if (i_pb >= n_N && w * wprev <= 0.)
prev = fmax2(fabs(adj),fpu);
R_ifDEBUG_printf("N(i=%2d): u=%#20.16g, pb(e^u)=%#12.6g, w=%#15.9g, %s prev=%11g,",
i_pb, u, y, w, (w * wprev <= 0.) ? "new" : "old", prev);
g = 1;
for (i_inn=0; i_inn < 1000; i_inn++) {
adj = g * w;
// take full Newton steps at the beginning; only then safe guard:
if (i_pb < n_N || fabs(adj) < prev) {
u_n = u - adj; // u_{n+1} = u_n - g*w
if (u_n <= 0.) { // <==> 0 < xinbta := e^u <= 1
if (prev <= acu || fabs(w) <= acu) {
/* R_ifDEBUG_printf(" -adj=%g, %s <= acu ==> convergence\n", */
/* -adj, (prev <= acu) ? "prev" : "|w|"); */
R_ifDEBUG_printf(" it{in}=%d, -adj=%g, %s <= acu ==> convergence\n",
i_inn, -adj, (prev <= acu) ? "prev" : "|w|");
goto L_converged;
}
// if (u_n != ML_NEGINF && u_n != 1)
break;
}
}
g /= 3;
}
// (cancellation in (u_n -u) => may differ from adj:
double D = fmin2(fabs(adj), fabs(u_n - u));
/* R_ifDEBUG_printf(" delta(u)=%g\n", u_n - u); */
R_ifDEBUG_printf(" it{in}=%d, delta(u)=%9.3g, D/|.|=%.3g\n",
i_inn, u_n - u, D/fabs(u_n + u));
if (D <= 4e-16 * fabs(u_n + u))
goto L_converged;
u = u_n;
xinbta = exp(u);
wprev = w;
} // for(i )
} else
for (i_pb=0; i_pb < 1000; i_pb++) {
y = pbeta_raw(xinbta, pp, qq, /*lower_tail = */ TRUE, log_p);
// delta{y} : d_y = y - (log_p ? la : a);
#ifdef IEEE_754
if(!R_FINITE(y) && !(log_p && y == ML_NEGINF))// y = -Inf is ok if(log_p)
#else
if (errno)
#endif
{ // ML_ERR_return_NAN :
ML_ERROR(ME_DOMAIN, "");
qb[0] = qb[1] = ML_NAN; return;
}
/* w := Newton step size (F(.) - a) / F'(.) or,
* -- log: (lF - la) / (F' / F) = exp(lF) * (lF - la) / F'
*/
w = log_p
? (y - la) * exp(y + logbeta + r * log(xinbta) + t * log1p(-xinbta))
: (y - a) * exp( logbeta + r * log(xinbta) + t * log1p(-xinbta));
if (i_pb >= n_N && w * wprev <= 0.)
prev = fmax2(fabs(adj),fpu);
R_ifDEBUG_printf("N(i=%2d): x0=%#17.15g, pb(x0)=%#17.15g, w=%#17.15g, %s prev=%g,",
i_pb, xinbta, y, w, (w * wprev <= 0.) ? "new" : "old", prev);
g = 1;
for (i_inn=0; i_inn < 1000;i_inn++) {
adj = g * w;
// take full Newton steps at the beginning; only then safe guard:
if (i_pb < n_N || fabs(adj) < prev) {
tx = xinbta - adj; // x_{n+1} = x_n - g*w
if (0. <= tx && tx <= 1.) {
if (prev <= acu || fabs(w) <= acu) {
R_ifDEBUG_printf(" it{in}=%d, delta(x)=%g, %s <= acu ==> convergence\n",
i_inn, -adj, (prev <= acu) ? "prev" : "|w|");
goto L_converged;
}
if (tx != 0. && tx != 1)
break;
}
}
g /= 3;
}
R_ifDEBUG_printf(" it{in}=%d, delta(x)=%g\n", i_inn, tx - xinbta);
if (fabs(tx - xinbta) <= 4e-16 * (tx + xinbta)) // "<=" : (.) == 0
goto L_converged;
xinbta = tx;
if(tx == 0) // "we have lost"
break;
wprev = w;
}
/*-- NOT converged: Iteration count --*/
warned = TRUE;
ML_ERROR(ME_PRECISION, "qbeta");
L_converged:
log_ = log_p || use_log_x; // only for printing
R_ifDEBUG_printf(" %s: Final delta(y) = %g%s\n",
warned ? "_NO_ convergence" : "converged",
y - (log_ ? la : a), (log_ ? " (log_)" : ""));
if((log_ && y == ML_NEGINF) || (!log_ && y == 0)) {
// stuck at left, try if smallest positive number is "better"
w = pbeta_raw(DBL_very_MIN, pp, qq, TRUE, log_);
if(log_ || fabs(w - a) <= fabs(y - a)) {
tx = DBL_very_MIN;
u_n = DBL_log_v_MIN;// = log(DBL_very_MIN)
}
add_N_step = FALSE; // not trying to do better anymore
}
else if(!warned && (log_ ? fabs(y - la) > 3 : fabs(y - a) > 1e-4)) {
if(!(log_ && y == ML_NEGINF &&
// e.g. qbeta(-1e-10, .2, .03, log=TRUE) cannot get accurate ==> do NOT warn
pbeta_raw(DBL_1__eps, // = 1 - eps
pp, qq, TRUE, TRUE) > la + 2))
MATHLIB_WARNING2( // low accuracy for more platform independent output:
"qbeta(a, *) =: x0 with |pbeta(x0,*%s) - alpha| = %.5g is not accurate",
(log_ ? ", log_" : ""), fabs(y - (log_ ? la : a)));
}
L_return:
if(give_log_q) { // ==> use_log_x , too
if(!use_log_x) // (see if claim above is true)
MATHLIB_WARNING(
"qbeta() L_return, u_n=%g; give_log_q=TRUE but use_log_x=FALSE -- please report!",
u_n);
double r = R_Log1_Exp(u_n);
if(swap_tail) {
qb[0] = r; qb[1] = u_n;
} else {
qb[0] = u_n; qb[1] = r;
}
} else {
if(use_log_x) {
if(add_N_step) {
/* add one last Newton step on original x scale, e.g., for
qbeta(2^-98, 0.125, 2^-96) */
xinbta = exp(u_n);
y = pbeta_raw(xinbta, pp, qq, /*lower_tail = */ TRUE, log_p);
w = log_p
? (y - la) * exp(y + logbeta + r * log(xinbta) + t * log1p(-xinbta))
: (y - a) * exp( logbeta + r * log(xinbta) + t * log1p(-xinbta));
tx = xinbta - w;
R_ifDEBUG_printf(
"Final Newton correction(non-log scale): xinbta=%.16g, y=%g, w=%g. => new tx=%.16g\n",
xinbta, y, w, tx);
} else {
if(swap_tail) {
qb[0] = -expm1(u_n); qb[1] = exp (u_n);
} else {
qb[0] = exp (u_n); qb[1] = -expm1(u_n);
}
return;
}
}
if(swap_tail) {
qb[0] = 1 - tx; qb[1] = tx;
} else {
qb[0] = tx; qb[1] = 1 - tx;
}
}
return;
}
double attribute_hidden
pnchisq_raw(double x, double f, double theta /* = ncp */,
double errmax, double reltol, int itrmax,
Rboolean lower_tail, Rboolean log_p)
{
double lam, x2, f2, term, bound, f_x_2n, f_2n;
double l_lam = -1., l_x = -1.; /* initialized for -Wall */
int n;
Rboolean lamSml, tSml, is_r, is_b, is_it;
LDOUBLE ans, u, v, t, lt, lu =-1;
if (x <= 0.) {
if(x == 0. && f == 0.) {
#define _L (-0.5 * theta) // = -lambda
return lower_tail ? R_D_exp(_L) : (log_p ? R_Log1_Exp(_L) : -expm1(_L));
}
/* x < 0 or {x==0, f > 0} */
return R_DT_0;
}
if(!R_FINITE(x)) return R_DT_1;
/* This is principally for use from qnchisq */
#ifndef MATHLIB_STANDALONE
R_CheckUserInterrupt();
#endif
if(theta < 80) { /* use 110 for Inf, as ppois(110, 80/2, lower.tail=FALSE) is 2e-20 */
LDOUBLE ans;
int i;
// Have pgamma(x,s) < x^s / Gamma(s+1) (< and ~= for small x)
// ==> pchisq(x, f) = pgamma(x, f/2, 2) = pgamma(x/2, f/2)
// < (x/2)^(f/2) / Gamma(f/2+1) < eps
// <==> f/2 * log(x/2) - log(Gamma(f/2+1)) < log(eps) ( ~= -708.3964 )
// <==> log(x/2) < 2/f*(log(Gamma(f/2+1)) + log(eps))
// <==> log(x) < log(2) + 2/f*(log(Gamma(f/2+1)) + log(eps))
if(lower_tail && f > 0. &&
log(x) < M_LN2 + 2/f*(lgamma(f/2. + 1) + _dbl_min_exp)) {
// all pchisq(x, f+2*i, lower_tail, FALSE), i=0,...,110 would underflow to 0.
// ==> work in log scale
double lambda = 0.5 * theta;
double sum, sum2, pr = -lambda;
sum = sum2 = ML_NEGINF;
/* we need to renormalize here: the result could be very close to 1 */
for(i = 0; i < 110; pr += log(lambda) - log(++i)) {
sum2 = logspace_add(sum2, pr);
sum = logspace_add(sum, pr + pchisq(x, f+2*i, lower_tail, TRUE));
if (sum2 >= -1e-15) /*<=> EXP(sum2) >= 1-1e-15 */ break;
}
ans = sum - sum2;
#ifdef DEBUG_pnch
REprintf("pnchisq(x=%g, f=%g, th.=%g); th. < 80, logspace: i=%d, ans=(sum=%g)-(sum2=%g)\n",
x,f,theta, i, (double)sum, (double)sum2);
#endif
return (double) (log_p ? ans : EXP(ans));
}
else {
LDOUBLE lambda = 0.5 * theta;
LDOUBLE sum = 0, sum2 = 0, pr = EXP(-lambda); // does this need a feature test?
/* we need to renormalize here: the result could be very close to 1 */
for(i = 0; i < 110; pr *= lambda/++i) {
// pr == exp(-lambda) lambda^i / i! == dpois(i, lambda)
sum2 += pr;
// pchisq(*, i, *) is strictly decreasing to 0 for lower_tail=TRUE
// and strictly increasing to 1 for lower_tail=FALSE
sum += pr * pchisq(x, f+2*i, lower_tail, FALSE);
if (sum2 >= 1-1e-15) break;
}
ans = sum/sum2;
#ifdef DEBUG_pnch
REprintf("pnchisq(x=%g, f=%g, theta=%g); theta < 80: i=%d, sum=%g, sum2=%g\n",
x,f,theta, i, (double)sum, (double)sum2);
#endif
return (double) (log_p ? LOG(ans) : ans);
}
} // if(theta < 80)
// else: theta == ncp >= 80 --------------------------------------------
#ifdef DEBUG_pnch
REprintf("pnchisq(x=%g, f=%g, theta=%g >= 80): ",x,f,theta);
#endif
// Series expansion ------- FIXME: log_p=TRUE, lower_tail=FALSE only applied at end
lam = .5 * theta;
lamSml = (-lam < _dbl_min_exp);
if(lamSml) {
/* MATHLIB_ERROR(
"non centrality parameter (= %g) too large for current algorithm",
theta) */
u = 0;
lu = -lam;/* == ln(u) */
l_lam = log(lam);
} else {
u = exp(-lam);
}
/* evaluate the first term */
v = u;
x2 = .5 * x;
f2 = .5 * f;
f_x_2n = f - x;
#ifdef DEBUG_pnch
REprintf("-- v=exp(-th/2)=%g, x/2= %g, f/2= %g\n",v,x2,f2);
#endif
if(f2 * DBL_EPSILON > 0.125 && /* very large f and x ~= f: probably needs */
FABS(t = x2 - f2) < /* another algorithm anyway */
sqrt(DBL_EPSILON) * f2) {
/* evade cancellation error */
/* t = exp((1 - t)*(2 - t/(f2 + 1))) / sqrt(2*M_PI*(f2 + 1));*/
lt = (1 - t)*(2 - t/(f2 + 1)) - M_LN_SQRT_2PI - 0.5 * log(f2 + 1);
#ifdef DEBUG_pnch
REprintf(" (case I) ==> ");
#endif
}
else {
/* Usual case 2: careful not to overflow .. : */
lt = f2*log(x2) -x2 - lgammafn(f2 + 1);
}
#ifdef DEBUG_pnch
REprintf(" lt= %g", lt);
#endif
tSml = (lt < _dbl_min_exp);
if(tSml) {
#ifdef DEBUG_pnch
REprintf(" is very small\n");
#endif
if (x > f + theta + 5* sqrt( 2*(f + 2*theta))) {
/* x > E[X] + 5* sigma(X) */
return R_DT_1; /* FIXME: could be more accurate than 0. */
} /* else */
l_x = log(x);
ans = term = 0.; t = 0;
}
else {
t = EXP(lt);
#ifdef DEBUG_pnch
REprintf(", t=exp(lt)= %g\n", t);
#endif
ans = term = (double) (v * t);
}
for (n = 1, f_2n = f + 2., f_x_2n += 2.; ; n++, f_2n += 2, f_x_2n += 2) {
#ifdef DEBUG_pnch_n
REprintf("\n _OL_: n=%d",n);
#endif
#ifndef MATHLIB_STANDALONE
if(n % 1000) R_CheckUserInterrupt();
#endif
/* f_2n === f + 2*n
* f_x_2n === f - x + 2*n > 0 <==> (f+2n) > x */
if (f_x_2n > 0) {
/* find the error bound and check for convergence */
bound = (double) (t * x / f_x_2n);
#ifdef DEBUG_pnch_n
REprintf("\n L10: n=%d; term= %g; bound= %g",n,term,bound);
#endif
is_r = is_it = FALSE;
/* convergence only if BOTH absolute and relative error < 'bnd' */
if (((is_b = (bound <= errmax)) &&
(is_r = (term <= reltol * ans))) || (is_it = (n > itrmax)))
{
#ifdef DEBUG_pnch
REprintf("BREAK n=%d %s; bound= %g %s, rel.err= %g %s\n",
n, (is_it ? "> itrmax" : ""),
bound, (is_b ? "<= errmax" : ""),
term/ans, (is_r ? "<= reltol" : ""));
#endif
break; /* out completely */
}
}
/* evaluate the next term of the */
/* expansion and then the partial sum */
if(lamSml) {
lu += l_lam - log(n); /* u = u* lam / n */
if(lu >= _dbl_min_exp) {
/* no underflow anymore ==> change regime */
#ifdef DEBUG_pnch_n
REprintf(" n=%d; nomore underflow in u = exp(lu) ==> change\n",
n);
#endif
v = u = EXP(lu); /* the first non-0 'u' */
lamSml = FALSE;
}
} else {
u *= lam / n;
v += u;
}
if(tSml) {
lt += l_x - log(f_2n);/* t <- t * (x / f2n) */
if(lt >= _dbl_min_exp) {
/* no underflow anymore ==> change regime */
#ifdef DEBUG_pnch
REprintf(" n=%d; nomore underflow in t = exp(lt) ==> change\n", n);
#endif
t = EXP(lt); /* the first non-0 't' */
tSml = FALSE;
}
} else {
t *= x / f_2n;
}
if(!lamSml && !tSml) {
term = (double) (v * t);
ans += term;
}
} /* for(n ...) */
if (is_it) {
MATHLIB_WARNING2(_("pnchisq(x=%g, ..): not converged in %d iter."),
x, itrmax);
}
#ifdef DEBUG_pnch
REprintf("\n == L_End: n=%d; term= %g; bound=%g\n",n,term,bound);
#endif
double dans = (double) ans;
return R_DT_val(dans);
}
