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 probabilities in P. P and 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 integers, and the values in P must lie in the interval [0 1].
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 output X is the value whose cumulative probability under the chi-square cdf defined by the corresponding degrees of freedom parameter in V is specified by the corresponding value in P.
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.