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# Test a truncation range that is completely above the mean.
parameters = 0.0, 1.0, 5.0, Infinity
mean = 5.18650396712584211561650896200523673
variance = 0.0326964346171122253453158077009336653
lower = 5
upper = Infinity
# Computed using Python with SciPy v1.6.0: truncnorm(5, inf)
# a, b = 5, float('inf')
# truncnorm.var(a, b)
cdf.points = \
  5, 5.00568241254803, 5.18650396728068, 5.36732552203467, 5.54814707752324,\
  5.72896863159791, 5.90979018980065, 6.09061174555624, Infinity
cdf.values = \
  0.                 , 0.02905695902309169, 0.6262388168228976 ,\
  0.8606099542475493 , 0.9496404359712429 , 0.9823752797552957 ,\
  0.9940250852662816 , 0.9980380355514441 , 1.
pdf.values = \
  5.186503967125854   , 5.041137006347447   , 2.006010972720016   ,\
  0.7725706879510773  , 0.2879673607116971  , 0.10388394357314994 ,\
  0.03627051296078461 , 0.012256291809202381, 0.

# Overridden tolerances
moments.relative = 1e-13
cdf.relative = 1e-12
cdf.mapping.relative = 6e-9
sf.relative = 1e-13
logpdf.relative = 1e-13
