tpdf — Evaluate the Student's t probability density function.

tpdf(x,nu) evaluates the probability density of the Student's t distribution with nu degrees of freedom at x.

Syntax

y = tpdf(x, nu)

Inputs

NameTypeRequiredDefaultDescription
xAnyYesEvaluation point.
nuAnyYesDegrees of freedom parameter.

Returns

NameTypeDescription
yNumericArrayDistribution function value.

Errors

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

How tpdf works

  • x and nu may be scalars or matching-size numeric arrays.
  • Scalar inputs broadcast over matching-size array inputs.
  • Nonpositive or NaN degrees of freedom produce NaN elementwise.
  • nu = Inf uses the standard normal density.

Example

Cauchy density at zero

y = tpdf(0, 1)

Using tpdf with coding agents

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

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

FAQ

What is nu?

nu is the degrees-of-freedom parameter for the Student's t distribution.

Open-source implementation

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

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