print('\n')
dta = list(dta.values()[-1])
print(dta[lrange(5), :])
print('\n')
#Create the KaplanMeier object and fit the model
km = KaplanMeier(dta, 0)
km.fit()
#show the results
km.plot()
print('basic model')
print('\n')
km.summary()
print('\n')
#Mutiple survival curves
km2 = KaplanMeier(dta, 0, exog=1)
km2.fit()
print('more than one curve')
print('\n')
km2.summary()
print('\n')
km2.plot()
#with censoring
censoring = np.ones_like(dta[:, 0])
print '\n' dta = dta.values()[-1] print dta[range(5),:] print '\n' #Create the KaplanMeier object and fit the model km = KaplanMeier(dta,0) km.fit() #show the results km.plot() print 'basic model' print '\n' km.summary() print '\n' #Mutiple survival curves km2 = KaplanMeier(dta,0,exog=1) km2.fit() print 'more than one curve' print '\n' km2.summary() print '\n' km2.plot() #with censoring censoring = np.ones_like(dta[:,0])
