Exemplo n.º 1
0
def test_squared_normal_chi2():
    #'\nsquare of standard normal random variable is chisquare with dof=1 distributed'
    cdftr = squarenormalg.cdf(xx,loc=l, scale=s)
    sfctr = 1-squarenormalg.sf(xx,loc=l, scale=s) #sf complement
    cdfst = stats.chi2.cdf(xx,1)
    assert_almost_equal(cdfst, cdftr, 14)
    assert_almost_equal(cdfst, sfctr, 14)
Exemplo n.º 2
0
def test_squared_normal_chi2():
    #'\nsquare of standard normal random variable is chisquare with dof=1 distributed'
    cdftr = squarenormalg.cdf(xx, loc=l, scale=s)
    sfctr = 1 - squarenormalg.sf(xx, loc=l, scale=s)  #sf complement
    cdfst = stats.chi2.cdf(xx, 1)
    assert_almost_equal(cdfst, cdftr, 14)
    assert_almost_equal(cdfst, sfctr, 14)
Exemplo n.º 3
0
#    print 'chi2    cdf with loc scale', stats.chi2.cdf(xx,1,loc=-10, scale=20)



if __name__ == '__main__':

    #Examples for Transf2_gen, u- or hump shaped transformation
    #copied from transformtwo.py
    l,s = 0.0, 1.0
    ppfq = [0.1, 0.5, 0.9]
    xx = [0.95, 1.0, 1.1]
    nxx = [-0.95, -1.0, -1.1]
    print
    #print invnormalg.__doc__
    print '\nsquare of standard normal random variable is chisquare with dof=1 distributed'
    print 'sqnorm  cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), squarenormalg.cdf(xx,loc=l, scale=s)
    print 'sqnorm 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), 1-squarenormalg.sf(xx,loc=l, scale=s)
    print 'chi2    cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.cdf(xx,1)
    print 'sqnorm  pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), squarenormalg.pdf(xx,loc=l, scale=s)
    print 'chi2    pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.pdf(xx,1)
    print 'sqnorm  ppf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), squarenormalg.ppf(ppfq,loc=l, scale=s)
    print 'chi2    ppf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.ppf(ppfq,1)
    print 'sqnorm  cdf with loc scale', squarenormalg.cdf(xx,loc=-10, scale=20)
    print 'chi2    cdf with loc scale', stats.chi2.cdf(xx,1,loc=-10, scale=20)
#    print 'cdf for [0.5]:', squarenormalg.cdf(0.5,loc=l, scale=s)
#    print 'chi square distribution'
#    print 'chi2 pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.pdf(xx,1)
#    print 'cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.cdf(xx,1)

    print '\nabsolute value of standard normal random variable is foldnorm(0) and '
    print 'halfnorm distributed:'
Exemplo n.º 4
0
#    print 'sqnorm  cdf with loc scale', squarenormalg.cdf(xx,loc=-10, scale=20)
#    print 'chi2    cdf with loc scale', stats.chi2.cdf(xx,1,loc=-10, scale=20)

if __name__ == '__main__':

    #Examples for Transf2_gen, u- or hump shaped transformation
    #copied from transformtwo.py
    l, s = 0.0, 1.0
    ppfq = [0.1, 0.5, 0.9]
    xx = [0.95, 1.0, 1.1]
    nxx = [-0.95, -1.0, -1.1]
    print
    #print invnormalg.__doc__
    print '\nsquare of standard normal random variable is chisquare with dof=1 distributed'
    print 'sqnorm  cdf for (%3.2f, %3.2f, %3.2f):' % tuple(
        xx), squarenormalg.cdf(xx, loc=l, scale=s)
    print 'sqnorm 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(
        xx), 1 - squarenormalg.sf(xx, loc=l, scale=s)
    print 'chi2    cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.cdf(
        xx, 1)
    print 'sqnorm  pdf for (%3.2f, %3.2f, %3.2f):' % tuple(
        xx), squarenormalg.pdf(xx, loc=l, scale=s)
    print 'chi2    pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.pdf(
        xx, 1)
    print 'sqnorm  ppf for (%3.2f, %3.2f, %3.2f):' % tuple(
        xx), squarenormalg.ppf(ppfq, loc=l, scale=s)
    print 'chi2    ppf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.ppf(
        ppfq, 1)
    print 'sqnorm  cdf with loc scale', squarenormalg.cdf(xx,
                                                          loc=-10,
                                                          scale=20)