Зміст курсу
Advanced Probability Theory
Advanced Probability Theory
Challenge: Estimate Parameters of Chi-square Distribution
Swipe to show code editor
Suppose that we have samples from the Chi-square distribution. We must determine the parameter K
of this distribution, which represents the number of degrees of freedom.
We know that the mathematical expectation of the Chi-square distributes value is equal to this parameter K.
Estimate this parameter using the method of moments and the maximum likelihood method. Since the number of degrees of freedom can only be discrete, round the resulting number to the nearest integer.
Your task is:
- Calculate the mean value over samples using
.mean()
method. - Use
.fit()
method to get maximum likelihood estimation for the parameter.
Дякуємо за ваш відгук!
Challenge: Estimate Parameters of Chi-square Distribution
Swipe to show code editor
Suppose that we have samples from the Chi-square distribution. We must determine the parameter K
of this distribution, which represents the number of degrees of freedom.
We know that the mathematical expectation of the Chi-square distributes value is equal to this parameter K.
Estimate this parameter using the method of moments and the maximum likelihood method. Since the number of degrees of freedom can only be discrete, round the resulting number to the nearest integer.
Your task is:
- Calculate the mean value over samples using
.mean()
method. - Use
.fit()
method to get maximum likelihood estimation for the parameter.
Дякуємо за ваш відгук!