Table of Contents
How do you calculate chi-square value in Matlab?
y = f ( x | ν ) = x ( ν − 2 ) / 2 e − x / 2 2 ν 2 Γ ( ν / 2 ) , where ν is the degrees of freedom and Γ( · ) is the Gamma function. For an example, see Compute Chi-Square Distribution pdf.
How do you create a chi-square distribution in Matlab?
r = chi2rnd( nu ) generates a random number from the chi-square distribution with nu degrees of freedom. r = chi2rnd( nu , sz1,…,szN ) generates an array of random numbers from the chi-square distribution, where sz1,…,szN indicates the size of each dimension.
How do you find goodness of fit in Matlab?
fit = goodnessOfFit( x , xref , cost_func ) returns the goodness of fit between the test data x and the reference data xref using the cost function cost_func . fit is a quantitative representation of the closeness of x to xref .
What is the CDF of the chi square distribution?
Cumulative Distribution Function The cumulative distribution function (cdf) of the chi-square distribution is where ν is the degrees of freedom and Γ (·) is the Gamma function. The result p is the probability that a single observation from the chi-square distribution with ν degrees of freedom falls in the interval [0, x].
How do I use the chi-square distribution?
Use generic distribution functions ( cdf, icdf, pdf, random) with a specified distribution name ( ‘Chisquare’) and parameters. The chi-square distribution uses the following parameter. ν = 1, 2, 3,… The degrees of freedom parameter is typically an integer, but chi-square functions accept any positive value.
What is the gamma function of the chi-square distribution?
The probability density function (pdf) of the chi-square distribution is where ν is the degrees of freedom and Γ ( · ) is the Gamma function. For an example, see Compute Chi-Square Distribution pdf. The cumulative distribution function (cdf) of the chi-square distribution is where ν is the degrees of freedom and Γ ( · ) is the Gamma function.
What is the inverse cumulative distribution function of the chi-square distribution (ICDF)?
The inverse cumulative distribution function (icdf) of the chi-square distribution is ν is the degrees of freedom, and Γ ( · ) is the Gamma function. The result p is the probability that a single observation from the chi-square distribution with ν degrees of freedom falls in the interval [0, x].