chi2cdf — Evaluate the chi-square cumulative distribution function.

chi2cdf(x,nu) evaluates the chi-square CDF at x for degrees of freedom nu. chi2cdf(x,nu,"upper") returns the complementary upper-tail probability.

Syntax

p = chi2cdf(x, nu)
p = chi2cdf(x, nu, "upper")

Inputs

NameTypeRequiredDefaultDescription
xAnyYesEvaluation point.
nuAnyYesDegrees of freedom parameter.

Returns

NameTypeDescription
yNumericArrayDistribution function value.

Errors

IdentifierWhenMessage
RunMat:chi2cdf:InvalidArgumentInputs are nonnumeric, sizes are incompatible, or too many arguments are supplied.normal distribution: invalid argument
RunMat:chi2cdf:InternalInternal tensor conversion or allocation fails.normal distribution: internal error

How chi2cdf works

  • x and nu support scalar expansion and matching array shapes.
  • nu must be positive; invalid parameters produce NaN outputs.
  • Negative x values return zero for the lower tail and one for the upper tail.
  • The computation uses regularized incomplete gamma functions.

Example

Evaluate chi-square CDF

p = chi2cdf(3,5)

Expected output:

p = 0.3000

Using chi2cdf with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how chi2cdf changes the result.

Run a small chi2cdf example, explain the result, then change one input and compare the output.

FAQ

Why use the upper-tail form?

The upper-tail form computes the complementary incomplete-gamma value directly, which is more stable for extreme upper tails than 1 - chi2cdf(...).

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how chi2cdf is executed, line by line, in Rust.

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