fastglmm
Massively scalable generalized linear mixed models
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qnorm_R.h File Reference
#include <cmath>

Go to the source code of this file.

Namespaces

namespace  glm

Macros

#define ML_NEGINF   std::numeric_limits<double>::min()
#define ML_POSINF   std::numeric_limits<double>::max()
#define NAN   std::numeric_limits<double>::quiet_NaN()
#define R_D_Lval(p)
#define R_DT_qIv(p)
#define R_Q_P01_boundaries(p, _LEFT_, _RIGHT_)

Macro Definition Documentation

◆ ML_NEGINF

#define ML_NEGINF   std::numeric_limits<double>::min()

◆ ML_POSINF

#define ML_POSINF   std::numeric_limits<double>::max()

◆ NAN

#define NAN   std::numeric_limits<double>::quiet_NaN()

◆ R_D_Lval

#define R_D_Lval ( p)
Value:
(lower_tail ? (p) : (0.5 - (p) + 0.5)) /* p */

◆ R_DT_qIv

#define R_DT_qIv ( p)
Value:
(log_p ? (lower_tail ? exp(p) : - expm1(p)) \
: R_D_Lval(p))
#define R_D_Lval(p)
Definition qnorm_R.h:66

◆ R_Q_P01_boundaries

#define R_Q_P01_boundaries ( p,
_LEFT_,
_RIGHT_ )
Value:
if (log_p) { \
if(p > 0) \
NAN; \
if(p == 0) /* upper bound*/ \
return lower_tail ? _RIGHT_ : _LEFT_; \
if(p == ML_NEGINF) \
return lower_tail ? _LEFT_ : _RIGHT_; \
} \
else { /* !log_p */ \
if(p < 0 || p > 1) \
NAN; \
if(p == 0) \
return lower_tail ? _LEFT_ : _RIGHT_; \
if(p == 1) \
return lower_tail ? _RIGHT_ : _LEFT_; \
}
#define NAN
Definition qnorm_R.h:61
#define ML_NEGINF
Definition qnorm_R.h:52