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('nsqnorm 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), 1 - negsquarenormalg.sf(xx, loc=l, scale=s)) print('nsqnorm pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), negsquarenormalg.pdf(xx, loc=l, scale=s)) print('nsqnorm cdf for (%3.2f, %3.2f, %3.2f):' % tuple(nxx), negsquarenormalg.cdf(nxx, loc=l, scale=s)) print('nsqnorm 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(nxx), 1 - negsquarenormalg.sf(nxx, loc=l, scale=s)) print('chi2 sf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.sf(xx, 1)) print('nsqnorm pdf for (%3.2f, %3.2f, %3.2f):' % tuple(nxx), negsquarenormalg.pdf(nxx, loc=l, scale=s)) print('chi2 pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.pdf(xx, 1)) print('nsqnorm pdf for (%3.2f, %3.2f, %3.2f):' % tuple(nxx), negsquarenormalg.pdf(nxx, 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('nsqnorm 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), 1-negsquarenormalg.sf(xx,loc=l, scale=s)) print('nsqnorm pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), negsquarenormalg.pdf(xx,loc=l, scale=s)) print('nsqnorm cdf for (%3.2f, %3.2f, %3.2f):' % tuple(nxx), negsquarenormalg.cdf(nxx,loc=l, scale=s)) print('nsqnorm 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(nxx), 1-negsquarenormalg.sf(nxx,loc=l, scale=s)) print('chi2 sf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.sf(xx,1)) print('nsqnorm pdf for (%3.2f, %3.2f, %3.2f):' % tuple(nxx), negsquarenormalg.pdf(nxx,loc=l, scale=s)) print('chi2 pdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), stats.chi2.pdf(xx,1)) print('nsqnorm pdf for (%3.2f, %3.2f, %3.2f):' % tuple(nxx), negsquarenormalg.pdf(nxx,loc=l, scale=s)) print('\nsquare of a t distributed random variable with dof=10 is') print(' F with dof=1,10 distributed') print('sqt cdf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), squaretg.cdf(xx,10)) print('sqt 1-sf for (%3.2f, %3.2f, %3.2f):' % tuple(xx), 1-squaretg.sf(xx,10))