Chi-square inverse cumulative distribution function
X = chi2inv(P,V)
X = chi2inv(P,V) computes the inverse of the
chi-square cdf with degrees of freedom specified by
V for the corresponding
V can be
vectors, matrices, or multidimensional arrays that have the same size. A scalar input is
expanded to a constant array with the same dimensions as the other inputs. The degrees of
freedom parameters in
V must be positive, and the values in
P must lie in the interval
The inverse chi-square cdf for a given probability p and ν degrees of freedom is
and Γ( · ) is the Gamma function. Each element of
X is the value whose cumulative probability
under the chi-square cdf defined by the corresponding degrees of freedom
V is specified by the corresponding
Find a value that exceeds 95% of the samples from a chi-square distribution with 10 degrees of freedom.
x = chi2inv(0.95,10) x = 18.3070
You would observe values greater than 18.3 only 5% of the time by chance.
This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).