//======================================================================
// rnorm_trunc( mu, sigma, lower, upper)
//
// generates one random normal RVs with mean 'mu' and standard
// deviation 'sigma', truncated to the interval (lower,upper), where
// lower can be -Inf and upper can be Inf.
//======================================================================
double
rnorm_trunc (double mu, double sigma, double lower, double upper)
{
int change;
double a, b;
double logt1 = log(0.150), logt2 = log(2.18), t3 = 0.725, t4 = 0.45;
double z, tmp, lograt;
change = 0;
a = (lower - mu)/sigma;
b = (upper - mu)/sigma;
// First scenario
if( (a == R_NegInf) || (b == R_PosInf))
{
if(a == R_NegInf)
{
change = 1;
a = -b;
b = R_PosInf;
}
// The two possibilities for this scenario
if(a <= 0.45) z = norm_rs(a, b);
else z = exp_rs(a, b);
if(change) z = -z;
}
// Second scenario
else if((a * b) <= 0.0)
{
// The two possibilities for this scenario
if((dnorm(a, 0.0, 1.0, 1) <= logt1) || (dnorm(b, 0.0, 1.0, 1) <= logt1))
{
z = norm_rs(a, b);
}
else z = unif_rs(a,b);
}
// Third scenario
else
{
if(b < 0)
{
tmp = b; b = -a; a = -tmp; change = 1;
}
lograt = dnorm(a, 0.0, 1.0, 1) - dnorm(b, 0.0, 1.0, 1);
if(lograt <= logt2) z = unif_rs(a,b);
else if((lograt > logt1) && (a < t3)) z = half_norm_rs(a,b);
else z = exp_rs(a,b);
if(change) z = -z;
}
return (sigma*z + mu);
}
void
rnorm_truncated (double *sample, int *n, double *mu,
double *sigma, double *lower, double *upper)
{
int k;
int change;
double a, b;
double logt1 = log(0.150), logt2 = log(2.18), t3 = 0.725, t4 = 0.45;
double z, tmp, lograt;
GetRNGstate();
for (k=0; k<(*n); k++)
{
change = 0;
a = (lower[k] - mu[k])/sigma[k];
b = (upper[k] - mu[k])/sigma[k];
// First scenario
if( (a == R_NegInf) || (b == R_PosInf))
{
if(a == R_NegInf)
{
change = 1;
a = -b;
b = R_PosInf;
}
// The two possibilities for this scenario
if(a <= 0.45) z = norm_rs(a, b);
else z = exp_rs(a, b);
if(change) z = -z;
}
// Second scenario
else if((a * b) <= 0.0)
{
// The two possibilities for this scenario
if((dnorm(a, 0.0, 1.0, 1) <= logt1) || (dnorm(b, 0.0, 1.0, 1) <= logt1))
{
z = norm_rs(a, b);
}
else z = unif_rs(a,b);
}
// Third scenario
else
{
if(b < 0)
{
tmp = b; b = -a; a = -tmp; change = 1;
}
lograt = dnorm(a, 0.0, 1.0, 1) - dnorm(b, 0.0, 1.0, 1);
if(lograt <= logt2) z = unif_rs(a,b);
else if((lograt > logt1) && (a < t3)) z = half_norm_rs(a,b);
else z = exp_rs(a,b);
if(change) z = -z;
}
sample[k] = sigma[k]*z + mu[k];
}
PutRNGstate();
}
void rnorm_truncated (double *sample, int *n, double *mu,
double *sigma, double *lower, double *upper)
{
int k;
int change = 0;
double a, b;
double logt1 = log(0.150), logt2 = log(2.18), t3 = 0.725, t4 = 0.45;
double z, tmp, lograt;
a = (*lower - *mu)/(*sigma);
b = (*upper - *mu)/(*sigma);
if(a==b) Rprintf("Warning!! a=%f, b=%f\n",a,b);
if(a>b) Rprintf("Warning!! a = %f > b = %f\n",a,b);
for (k=0; k<(*n); k++)
{
change=0;
// First scenario
if( (a == R_NegInf) || (b == R_PosInf))
{
if(a == R_NegInf)
{
change = 1;
a = -b;
b = R_PosInf;
}
// The two possibilities for this scenario
if(a <= t4) z = norm_rs(a, b);
else z = exp_rs(a, b);
if(change) z = -z;
}
// Second scenario
else if((a * b) <= 0.0)
{
// The two possibilities for this scenario
if((dnorm(a, 0.0, 1.0, 1) <= logt1) || (dnorm(b, 0.0, 1.0, 1) <= logt1))
{
z = norm_rs(a, b);
}
else z = unif_rs(a,b);
}
// Third scenario
else
{
if(b < 0)
{
tmp = b; b = -a; a = -tmp; change = 1;
}
lograt = dnorm(a, 0.0, 1.0, 1) - dnorm(b, 0.0, 1.0, 1);
if(lograt <= logt2) z = unif_rs(a,b);
else if((lograt > logt1) && (a < t3)) z = half_norm_rs(a,b);
else z = exp_rs(a,b);
if(change) z = -z;
}
sample[k] = *sigma*z + *mu;
}
}
