def test_lmparams_glogistic(self):
"Test parameter estimation from L_moments for the generalized logistic distribution"
(loc, scl, shp) = (0.0, 1., 0.999)
lmoms = glogistic(shp, loc, scl,).lstats(4)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array((loc, scl, shp)), 6)
(loc, scl, shp) = (0.0, 0.5, -0.999)
lmoms = glogistic(shp, loc, scl).lstats(4)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array((loc, scl, shp)), 6)
(loc, scl, shp) = (0.5, 2.0, 0.5)
lmoms = glogistic(shp, loc, scl).lstats(4)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array((loc, scl, shp)), 6)
(loc, scl, shp) = (0, 2, 0)
lmoms = glogistic(shp, loc, scl).lstats(4)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array((loc, scl, shp)), 6)
#
lmoms = (-1., 1., 3.)
#self.failUnlessRaises(ValueError, pel_glogistic, lmoms)
lmoms = (-1., 1., 1./3)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array([-1.51901997, 0.82699334, -0.33333333]))
lmoms = (-1., 1., -0.9)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array([-0.01032489, 0.1092924, 0.9]))
lmoms = (-1., 1., +0.9)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array([-1.98967511, 0.1092924, -0.9]))
lmoms = (+1., +1., +0.7)
assert_almost_equal(np.array(glogistic.lmparams(lmoms)),
np.array([ 0.09697573, 0.36788301, -0.7]))
def test_ppf(self):
"Try the PPF of the glogistic distribution"
c = 0.
_glo = [-6.906754779, -1.098612289, 0.0, 6.906754779]
assert_almost_equal(glogistic(c).ppf([0.001, 0.25, 0.5, 0.999]), _glo)
c = 0.1
_glo = [-9.95062699, -1.16123174, 0.0, 4.98762620]
assert_almost_equal(glogistic(c).ppf([0.001, 0.25, 0.5, 0.999]), _glo)
c = 1.
_glo = [-998.0, -2.0, 0.0, 0.998998998999]
assert_almost_equal(glogistic(c).ppf([0.001, 0.25, 0.5, 0.999]), _glo)
def test_cdf(self):
"Try the CDF of the glogistic distribution"
c = 1.
_glo = [0.5, 0.57142857, 0.66666667, 1.0]
assert_almost_equal(glogistic(c).cdf([0., 0.25, 0.5, 1.0]), _glo)
c = 0.1
_glo = [0.5, 0.56295858, 0.62549377, 0.74146659]
assert_almost_equal(glogistic(c).cdf([0., 0.25, 0.5, 1.0]), _glo)
c = 0.
_glo = [0.5, 0.5621765009, 0.622459331, 0.7310585786]
assert_almost_equal(glogistic(c).cdf([0., 0.25, 0.5, 1.0]), _glo)
def test_ppf(self):
"Try the PPF of the glogistic distribution"
c = 0.
_glo = [-6.906754779, -1.098612289, 0.0, 6.906754779]
assert_almost_equal(glogistic(c).ppf([0.001, 0.25, 0.5, 0.999]), _glo)
c = 0.1
_glo = [-9.95062699, -1.16123174, 0.0, 4.98762620]
assert_almost_equal(glogistic(c).ppf([0.001, 0.25, 0.5, 0.999]), _glo)
c = 1.
_glo = [-998.0, -2.0, 0.0, 0.998998998999]
assert_almost_equal(glogistic(c).ppf([0.001, 0.25, 0.5, 0.999]), _glo)
def test_cdf(self):
"Try the CDF of the glogistic distribution"
c = 1.
_glo = [0.5, 0.57142857, 0.66666667, 1.0]
assert_almost_equal(glogistic(c).cdf([0., 0.25, 0.5, 1.0]), _glo)
c = 0.1
_glo = [0.5, 0.56295858, 0.62549377, 0.74146659]
assert_almost_equal(glogistic(c).cdf([0., 0.25, 0.5, 1.0]), _glo)
c = 0.
_glo = [0.5, 0.5621765009, 0.622459331, 0.7310585786]
assert_almost_equal(glogistic(c).cdf([0., 0.25, 0.5, 1.0]), _glo)
def test_lmparams_glogistic(self):
"Test parameter estimation from L_moments for the generalized logistic distribution"
(loc, scl, shp) = (0.0, 1., 0.999)
lmoms = glogistic(
shp,
loc,
scl,
).lstats(4)
assert_almost_equal(glogistic.lmparams(lmoms), np.array(
(loc, scl, shp)), 6)
(loc, scl, shp) = (0.0, 0.5, -0.999)
lmoms = glogistic(shp, loc, scl).lstats(4)
assert_almost_equal(glogistic.lmparams(lmoms), np.array(
(loc, scl, shp)), 6)
(loc, scl, shp) = (0.5, 2.0, 0.5)
lmoms = glogistic(shp, loc, scl).lstats(4)
assert_almost_equal(glogistic.lmparams(lmoms), np.array(
(loc, scl, shp)), 6)
(loc, scl, shp) = (0, 2, 0)
lmoms = glogistic(shp, loc, scl).lstats(4)
assert_almost_equal(glogistic.lmparams(lmoms), np.array(
(loc, scl, shp)), 6)
#
lmoms = (-1., 1., 3.)
#self.failUnlessRaises(ValueError, pel_glogistic, lmoms)
lmoms = (-1., 1., 1. / 3)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array([-1.51901997, 0.82699334, -0.33333333]))
lmoms = (-1., 1., -0.9)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array([-0.01032489, 0.1092924, 0.9]))
lmoms = (-1., 1., +0.9)
assert_almost_equal(glogistic.lmparams(lmoms),
np.array([-1.98967511, 0.1092924, -0.9]))
lmoms = (+1., +1., +0.7)
assert_almost_equal(np.array(glogistic.lmparams(lmoms)),
np.array([0.09697573, 0.36788301, -0.7]))