normcdf — Evaluate the normal cumulative distribution function.

normcdf(x) evaluates the standard normal CDF. normcdf(x,mu) and normcdf(x,mu,sigma) evaluate a normal distribution with mean mu and standard deviation sigma. normcdf(...,"upper") returns the upper-tail probability.

Syntax

p = normcdf(x)
p = normcdf(x, mu)
p = normcdf(x, mu, sigma)
p = normcdf(x, mu, sigma, "upper")

Inputs

NameTypeRequiredDefaultDescription
xAnyYesEvaluation point.
muAnyNo0Mean parameter.
sigmaAnyNo1Standard deviation parameter.

Returns

NameTypeDescription
yNumericArrayDistribution function value.

Errors

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

How normcdf works

  • x, mu, and sigma may be scalars or matching-size numeric arrays.
  • Negative sigma values produce NaN elementwise.
  • sigma = 0 returns a step at mu.
  • "upper" uses the complementary error-function path for better extreme-tail stability.

Examples

Standard normal midpoint

p = normcdf(0)

Upper tail

p = normcdf(8, 0, 1, "upper")

Using normcdf with coding agents

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

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

FAQ

Does normcdf support array inputs?

Yes. Scalar parameters broadcast over matching-size numeric arrays.

Open-source implementation

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

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