Student T-Distribution Sampler

Draw Student-t samples as standard normal divided by the square root of an independent chi-square ratio.

Description

Draw Student-t samples as standard normal divided by the square root of an independent chi-square ratio.

Student T-Distribution Sampler: Draw Student-t samples as standard normal divided by the square root of an independent chi-square ratio.

When to use Student T-Distribution Sampler

Use this probability or sampling tool to compute a stated quantity or generate reproducible draws from a precisely parameterized distribution or stochastic model.

degrees Of Freedom
Required number input.
Sample count
Required integer input.
Seed
Required string input.

How Student T-Distribution Sampler works

Draw Student-t samples as standard normal divided by the square root of an independent chi-square ratio. The tool evaluates the supplied inputs together and returns the named outputs below; it does not infer omitted operating conditions or change the units shown.1

Samples
The resulting samples returned as a list.

Limitations and assumptions

  • Results depend on parameterization, support, random source, seed, convergence, burn-in, autocorrelation, proposal quality, normalization, numerical tails, and whether model assumptions match the process. Samples are not exact evidence of convergence.
  • Use finite inputs in the displayed units and preserve more precision than the final presentation requires. Independently verify safety-critical, financial, compliance, or production decisions.

Alternative or Complementary approaches

Check analytic moments or known test cases, use independent chains and diagnostics for Monte Carlo methods, report seed and effective sample size, and inspect tail behavior.

References

  1. Probability distribution — Wikipedia contributors

Similar or alternative tools

  • F-Distribution Sampler

    Draw an F ratio from two independent chi-square variates, each divided by its degrees of freedom.

  • Rejection Sampler

    Draw reproducible standard-normal samples truncated to an interval using uniform rejection sampling.

  • Chi-Square Distribution Sampler

    Sample chi-square variates as gamma(shape=df/2, scale=2) with positive degrees of freedom.

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