binornd — Generate binomially-distributed random samples.

binornd(n,p) generates binomial random samples for number of trials n and success probability p. Size-vector and dimension-list forms are supported.

Syntax

r = binornd(n, p)
r = binornd(n, p, sz)
r = binornd(n, p, sz1, sz2, ...)

Inputs

NameTypeRequiredDefaultDescription
nAnyYesNumber of Bernoulli trials.
pAnyYesSuccess probability for each trial.
szAnyVariadicOutput size arguments.

Returns

NameTypeDescription
rNumericArrayRandom sample array.

Errors

IdentifierWhenMessage
RunMat:binornd:InvalidArgumentInput parameters or size arguments are missing, malformed, or incompatible.distribution random: invalid argument
RunMat:binornd:InternalInternal tensor conversion, allocation, or RNG state access fails.distribution random: internal error

How binornd works

  • n and p support scalar expansion and matching array shapes.
  • Without explicit size arguments, the output shape is the scalar-expanded parameter shape.
  • With explicit size arguments, nonscalar parameters must match the requested shape.
  • n must be a nonnegative integer and p must be in [0,1].

Example

Generate binomial samples

r = binornd(10,0.5,2,3)

Using binornd with coding agents

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

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

FAQ

Can n be fractional?

No. RunMat requires n to be a nonnegative integer trial count.

Open-source implementation

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

About RunMat

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