# 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:')
print('absnorm cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx),
absnormalg.cdf(xx, loc=l, scale=s))
print('absnorm 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(xx),
1 - absnormalg.sf(xx, loc=l, scale=s))
print('foldn cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx),
stats.foldnorm.cdf(xx, 1e-5))
print('halfn cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx),
stats.halfnorm.cdf(xx))
print('absnorm pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx),
absnormalg.pdf(xx, loc=l, scale=s))
print('foldn pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx),
stats.foldnorm.pdf(xx, 1e-5))
print('halfn pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx),
stats.halfnorm.pdf(xx))
print('absnorm ppf for (%3.2f, %3.2f, %3.2f):' % tuple(ppfq),
absnormalg.ppf(ppfq, loc=l, scale=s))
print('foldn ppf for (%3.2f, %3.2f, %3.2f):' % tuple(ppfq),
stats.foldnorm.ppf(ppfq, 1e-5))
print('halfn ppf for (%3.2f, %3.2f, %3.2f):' % tuple(ppfq),
stats.halfnorm.ppf(ppfq))
# 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('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:')
print('absnorm cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), absnormalg.cdf(xx,loc=l, scale=s))
print('absnorm 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), 1-absnormalg.sf(xx,loc=l, scale=s))
print('foldn cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.foldnorm.cdf(xx,1e-5))
print('halfn cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.halfnorm.cdf(xx))
print('absnorm pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), absnormalg.pdf(xx,loc=l, scale=s))
print('foldn pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.foldnorm.pdf(xx,1e-5))
print('halfn pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.halfnorm.pdf(xx))
print('absnorm ppf for (%3.2f, %3.2f, %3.2f):' % tuple(ppfq), absnormalg.ppf(ppfq,loc=l, scale=s))
print('foldn ppf for (%3.2f, %3.2f, %3.2f):' % tuple(ppfq), stats.foldnorm.ppf(ppfq,1e-5))
print('halfn ppf for (%3.2f, %3.2f, %3.2f):' % tuple(ppfq), stats.halfnorm.ppf(ppfq))
# 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('\nnegative square of standard normal random variable is')
print('1-chisquare with dof=1 distributed')
print('this is mainly for testing')
print('the following should be outside of the support - returns nan')
print('nsqnorm cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), negsquarenormalg.cdf(xx,loc=l, scale=s))
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:')
print('absnorm cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), absnormalg.cdf(xx,loc=l, scale=s))
print('absnorm 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), 1-absnormalg.sf(xx,loc=l, scale=s))
print('foldn cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.foldnorm.cdf(xx,1e-5))
print('halfn cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.halfnorm.cdf(xx))
print('absnorm pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), absnormalg.pdf(xx,loc=l, scale=s))
print('foldn pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.foldnorm.pdf(xx,1e-5))
print('halfn pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.halfnorm.pdf(xx))
print('absnorm ppf for (%3.2f, %3.2f, %3.2f):' % tuple(ppfq), absnormalg.ppf(ppfq,loc=l, scale=s))
print('foldn ppf for (%3.2f, %3.2f, %3.2f):' % tuple(ppfq), stats.foldnorm.ppf(ppfq,1e-5))
print('halfn ppf for (%3.2f, %3.2f, %3.2f):' % tuple(ppfq), stats.halfnorm.ppf(ppfq))
# 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('\nnegative square of standard normal random variable is')
print('1-chisquare with dof=1 distributed')
print('this is mainly for testing')
print('the following should be outside of the support - returns nan')
print('nsqnorm cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), negsquarenormalg.cdf(xx,loc=l, scale=s))