With the help of stats.halfgennorm.fit() method, we can get the parameter estimates for generic data by using stats.halfgennorm.fit() method.
Syntax :
stats.halfgennorm.fit(data, beta)
Return : Return the parameter estimates for generic data.
Example #1 :
In this example we can see that by using stats.halfgennorm.fit() method, we are able to get the parameter estimates for generic data by using this method.
# import halfgennorm from scipy.stats import halfgennorm beta = 1data = [1, 2, 3, 4] # Using stats.halfgennorm.fit() method gfg = halfgennorm.fit(data, beta) print(gfg) |
Output :
(0.747842031646833, 0.999999999643278, 0.9104743888803231)
Example #2 :
# import halfgennorm from scipy.stats import halfgennorm beta = 4data = [1, 2, 3, 4] # Using stats.halfgennorm.fit() method gfg = halfgennorm.fit(data, beta) print(gfg) |
Output :
(283.5624794926913, 0.9950868221655309, 3.0513233113282805)
