tpdf

Student's t probability density function

Syntax

y = tpdf(x,nu)


Description

y = tpdf(x,nu) returns the probability density function (pdf) of the Student's t distribution at each of the values in x using the corresponding degrees of freedom in nu. x and nu can be vectors, matrices, or multidimensional arrays that have the same size. A scalar input is expanded to a constant array with the same dimensions as the other inputs.

Examples

Compute Student's t pdf

The mode of the Student's t distribution is at x = 0. This example shows that the value of the function at the mode is an increasing function of the degrees of freedom.

tpdf(0,1:6)

ans = 1×6

    0.3183    0.3536    0.3676    0.3750    0.3796    0.3827

The t distribution converges to the standard normal distribution as the degrees of freedom approaches infinity. How good is the approximation for $$\nu$$ equal to 30?

difference = tpdf(-2.5:2.5,30)-normpdf(-2.5:2.5)

difference = 1×6

    0.0035   -0.0006   -0.0042   -0.0042   -0.0006    0.0035

More About

Student’s t pdf

The probability density function (pdf) of the Student's t distribution is

$$y=f(x|\nu )=\frac{\Gamma \left(\frac{\nu +1}{2}\right)}{\Gamma \left(\frac{\nu }{2}\right)}\frac{1}{\sqrt{\nu \pi }}\frac{1}{{\left(1+\frac{x^2}{\nu }\right)}^{\frac{\nu +1}{2}}}$$

where ν is the degrees of freedom and Γ( · ) is the Gamma function. The result y is the probability of observing a particular value of x from a Student’s t distribution with ν degrees of freedom.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).