double critchi (int df, double p)
/* Perlman. arguments interchanged */
{
double minchisq = 0.0;
double maxchisq = 100.0*p;
double chisqval, z, y ;;
if (p <= 0.0)
return (maxchisq);
else if (p >= 1.0)
return (0.0);
if (df==1) {
z = zprob(0.5*p) ;
return z*z ;
}
if (df==2) {
y = -log(p) ;
return 2*y ;
}
chisqval = df / sqrt (p); /* fair first value */
while (maxchisq - minchisq > CHI_EPSILON)
{
if (rtlchsq (df, chisqval) < p)
maxchisq = chisqval;
else
minchisq = chisqval;
chisqval = (maxchisq + minchisq) * 0.5;
}
return (chisqval);
}
double zprob(double ptail)
/** inverse normal */
{
double z, p, t, plog;
double ylo, yhi, ya, yb ;
int i, k ;
if (ztable == NULL) setzptable() ;
if (ptail==0.5) return 0.0 ;
if (ptail>0.5) {
z = zprob(1.0-ptail) ;
return -z ;
}
if ((ptail>.40) && (ptail < .50)) return znewt(0.0, ptail) ;
if (ptail<ptiny) {
z = zzprob(ptail) ;
return znewt(z,ptail) ;
}
/** replace by binary or interpolating search */
plog = -log(ptail) ;
k = firstgt(plog, ptable, numbox) ;
if (k==0) return ztable[0] ;
if (k==numbox) return ztable[numbox-1] ;
ylo = ptable[k-1] ;
yhi = ptable[k] ;
ya = (yhi-plog) ;
yb = plog-ylo ;
z = (ya*ztable[k-1]+yb*ztable[k])/(ya+yb) ;
if (isnan(z)) fatalx("zprob bug %15.9f %15.9f\n", z, ptail) ;
t = znewt(z, ptail) ;
if (isnan(t)) fatalx("zprob bug %15.9f %15.9f\n", z, ptail) ;
return t ;
}
double rantruncnorm(double T, int upper)
{
double u ;
if (upper==0) return -rantruncnorm(-T, 1) ;
u = DRAND2() ; if (u==0.0) u = 0.5 ; // tiny hack
u *= ntail(T) ;
if (u==0.0) return MAX(T, 50.0) ;
return zprob(u) ;
}
/*
Returns the (1-tailed) probability value associated with the provided
chi-square value and df. Adapted from chisq.c in Gary Perlman's |Stat.
*/
double chicdf(double chisq, int df)
{
const double BIG = 20.0;
double const pi = 3.141592653589793;
double a,c,e,s,y,z;
bool even = false;
int k = df /2;
if (chisq <=0 || df < 1)
return 1.0;
a = 0.5 * chisq;
if (df==(k*2))
even = true;
if (df > 1)
y = _exp(-a);
if (even)
s = y;
else
s = 2.0 * zprob(-sqrt(chisq));
if (df > 2)
{
double chisq1 = 0.5 * (df - 1.0);
if (even)
z = 1.0;
else
z = 0.5;
if (a > BIG)
{
if (even)
e = 0.0;
else
e = log(sqrt(pi));
c = log(a);
while (z <= chisq)
{
e = log(z) + e;
s = s + _exp(c*z-a-e);
z = z + 1.0;
}
return s;
}
else
{
if (even)
e = 1.0;
else
e = 1.0 / sqrt(pi) / sqrt(a);
c = 0.0;
while (z <= chisq)
{
e = e * (a/float(z));
c = c + e;
z = z + 1.0;
}
return (c*y+s);
}
}
else
return s;
}
