master
pbrod 9 years ago
parent e7d541400e
commit 00f3ce12d8

@ -23,7 +23,7 @@ from scipy import optimize
import numpy as np import numpy as np
from scipy.special import expm1, log1p from scipy.special import expm1, log1p
from numpy import (alltrue, arange, zeros, log, sqrt, exp, from numpy import (alltrue, arange, zeros, log, sqrt, exp,
atleast_1d, any, asarray, nan, pi, isfinite) any, asarray, nan, pi, isfinite)
from numpy import flatnonzero as nonzero from numpy import flatnonzero as nonzero
@ -1577,7 +1577,7 @@ def test1():
# 80% CI for x # 80% CI for x
Lx = ProfileQuantile(phat, x) Lx = ProfileQuantile(phat, x)
Lx.plot() Lx.plot()
x_ci = Lx.get_bounds(alpha=0.2) # x_ci = Lx.get_bounds(alpha=0.2)
plt.figure(5) plt.figure(5)
@ -1587,9 +1587,7 @@ def test1():
# 80% CI for x # 80% CI for x
Lsf = ProfileProbability(phat, np.log(sf)) Lsf = ProfileProbability(phat, np.log(sf))
Lsf.plot() Lsf.plot()
logsf_ci = Lsf.get_bounds(alpha=0.2) # logsf_ci = Lsf.get_bounds(alpha=0.2)
plt.show('hold') plt.show('hold')

Loading…
Cancel
Save