# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

parameters = 1.2 0.4
mean = Inf
variance = Inf
lower = 1.2
cdf.points = 1.2, 1.2001, 1.21, 1.225, 1.25, 1.3, 1.9, 3.4, 5.6
# Computed with matlab using and function plevy from rmutil package.
# 0 has been supplemented as R raises an error for x=mu;
# 'scipy.stats import levy' returns 0.
# Mathematica returns 0.
#
# Points 1.21, 1.225, 1.25 evaluate with low precision using R or scipy.
# They have been corrected using e.g.
# matlab = erfc(sqrt(0.4/(2*(1.21-1.2)))) = 2.5396285894709011e-10
cdf.values = \
  0, 0,\
  2.5396285894709011e-10,    6.3342483666242627e-05,\
  0.0046777349810472836,     4.5500263896358417171e-02,\
  4.4969179796889102718e-01, 6.6981535759941657204e-01,\
  7.6302460055299503594e-01
pdf.values = \
  0, 0,\
  5.2005637376544783034e-07, 2.1412836122382383069e-02,\
  4.1333970708184164522e-01, 1.0798193302637617563e+00,\
  3.2374931916108729002e-01, 7.0603255009363707906e-02,\
  2.6122839883975741693e-02
logpdf.values = \
  -Inf,   -1.9875615733413976614e+03,\
  -1.4469328620159595644e+01, -3.8437647179708118728e+00,\
  -8.8348548881076238715e-01,  7.6793740349318850846e-02,\
  -1.1277857689479373615e+00, -2.6506790305972467436e+00,\
  -3.6449452559826185372e+00
# Computed using WolframAlpha
cdf.hp.points = 1.205, 1.2049
cdf.hp.values = 3.7440973842063723e-19, 1.6388396909072308e-19
sf.hp.points = 1e39, 42e37
sf.hp.values = 1.5957691216057308e-20, 2.4623252122982907e-20
# As cdf.values above but with the redundant 0 removed
icdf.points = \
  0,\
  2.5396285894709011e-10,    6.3342483666242627e-05,\
  0.0046777349810472836,     4.5500263896358417171e-02,\
  4.4969179796889102718e-01, 6.6981535759941657204e-01,\
  7.6302460055299503594e-01
icdf.values = 1.2, 1.21, 1.225, 1.25, 1.3, 1.9, 3.4, 5.6

# Overridden tolerances
cdf.hp.relative = 5e-14
