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, 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
where
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.