# beta

## Syntax

``beta(x,y)``

## Description

example

````beta(x,y)` returns the beta function of `x` and `y`.```

## Examples

### Compute Beta Function for Numeric Inputs

Compute the beta function for these numbers. Because these numbers are not symbolic objects, you get floating-point results:

`[beta(1, 5), beta(3, sqrt(2)), beta(pi, exp(1)), beta(0, 1)]`
```ans = 0.2000 0.1716 0.0379 Inf```

### Compute Beta Function for Symbolic Inputs

Compute the beta function for the numbers converted to symbolic objects:

`[beta(sym(1), 5), beta(3, sym(2)), beta(sym(4), sym(4))]`
```ans = [ 1/5, 1/12, 1/140]```

If one or both parameters are complex numbers, convert these numbers to symbolic objects:

`[beta(sym(i), 3/2), beta(sym(i), i), beta(sym(i + 2), 1 - i)]`
```ans = [ (pi^(1/2)*gamma(1i))/(2*gamma(3/2 + 1i)), gamma(1i)^2/gamma(2i),... (pi*(1/2 + 1i/2))/sinh(pi)]```

### Compute Beta Function for Negative Parameters

Compute the beta function for negative parameters. If one or both arguments are negative numbers, convert these numbers to symbolic objects:

`[beta(sym(-3), 2), beta(sym(-1/3), 2), beta(sym(-3), 4), beta(sym(-3), -2)]`
```ans = [ 1/6, -9/2, Inf, Inf]```

### Compute Beta Function for Matrix Inputs

Call `beta` for the matrix `A` and the value `1`. The result is a matrix of the beta functions `beta(A(i,j),1)`:

```A = sym([1 2; 3 4]); beta(A,1)```
```ans = [ 1, 1/2] [ 1/3, 1/4]```

### Differentiate Beta Function

Differentiate the beta function, then substitute the variable t with the value 2/3 and approximate the result using `vpa`:

```syms t u = diff(beta(t^2 + 1, t)) vpa(subs(u, t, 2/3), 10)```
```u = beta(t, t^2 + 1)*(psi(t) + 2*t*psi(t^2 + 1) -... psi(t^2 + t + 1)*(2*t + 1)) ans = -2.836889094```

### Expand Beta Function

Expand these beta functions:

```syms x y expand(beta(x, y)) expand(beta(x + 1, y - 1))```
```ans = (gamma(x)*gamma(y))/gamma(x + y) ans = -(x*gamma(x)*gamma(y))/(gamma(x + y) - y*gamma(x + y))```

## Input Arguments

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Input, specified as a number, vector, matrix, or array, or a symbolic number, variable, array, function, or expression.

If `x` is a vector or matrix, `beta` returns the beta function for each element of `x`.

Input, specified as a number, vector, matrix, or array, or a symbolic number, variable, array, function, or expression.

If `y` is a vector or matrix, `beta` returns the beta function for each element of `y`.

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### Beta Function

This integral defines the beta function:

`$Β\left(x,y\right)=\underset{0}{\overset{1}{\int }}{t}^{x-1}{\left(1-t\right)}^{y-1}dt=\frac{\Gamma \left(x\right)\Gamma \left(y\right)}{\Gamma \left(x+y\right)}$`

## Tips

• The beta function is uniquely defined for positive numbers and complex numbers with positive real parts. It is approximated for other numbers.

• Calling `beta` for numbers that are not symbolic objects invokes the MATLAB® `beta` function. This function accepts real arguments only. If you want to compute the beta function for complex numbers, use `sym` to convert the numbers to symbolic objects, and then call `beta` for those symbolic objects.

• If one or both parameters are negative numbers, convert these numbers to symbolic objects using `sym`, and then call `beta` for those symbolic objects.

• If the beta function has a singularity, `beta` returns the positive infinity `Inf`.

• `beta(sym(0),0)`, `beta(0,sym(0))`, and `beta(sym(0),sym(0))` return `NaN`.

• `beta(x,y) = beta(y,x)` and ```beta(x,A) = beta(A,x)```.

• At least one input argument must be a scalar or both arguments must be vectors or matrices of the same size. If one input argument is a scalar and the other one is a vector or a matrix, `beta(x,y)` expands the scalar into a vector or matrix of the same size as the other argument with all elements equal to that scalar.

 Zelen, M. and N. C. Severo. “Probability Functions.” Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. (M. Abramowitz and I. A. Stegun, eds.). New York: Dover, 1972.

## Support

#### Mathematical Modeling with Symbolic Math Toolbox

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