# MarcumQ

MarcumQ[m,a,b]

gives Marcum's Q function .

MarcumQ[m,a,b0,b1]

gives Marcum's Q function .

# Details • Mathematical function suitable for both symbolic and numerical evaluation.
• for real positive , , and .
• MarcumQ[m,a,b] is an entire function of both a and b with no branch cut discontinuities.
• For a certain special argument, MarcumQ automatically evaluates to exact values.
• MarcumQ can be evaluated to arbitrary numerical precision.
• MarcumQ automatically threads over lists.

# Examples

open allclose all

## Basic Examples(4)

Evaluate numerically:

Plot over a subset of the reals:

Plot over a subset of the complexes:

Series expansion at the origin:

## Scope(21)

### Numerical Evaluation(4)

Evaluate numerically:

Evaluate to high precision:

The precision of the output tracks the precision of the input:

Complex number input:

Evaluate efficiently at high precision:

### Specific Values(2)

MarcumQ for symbolic a:

Find the maximum of MarcumQ[1,2,x]:

### Visualization(2)

Plot the MarcumQ function for various parameters:

Plot the real part of :

Plot the imaginary part of :

### Function Properties(9)

Real domain of MarcumQ:

Complex domain of MarcumQ:

Approximate function range of : is an even function of : is an analytic function of and for positive integer :

It has no singularities or discontinuities: is neither non-increasing nor non-decreasing: is not injective: is non-negative: is neither convex nor concave:

### Differentiation(2)

First derivative with respect to a:

First derivative with respect to b:

Higher derivatives with respect to a:

Plot the higher derivatives with respect to a when b=3 and m=1:

### Series Expansions(2)

Find the Taylor expansion using Series:

Plots of the first three approximations around :

Taylor expansion at a generic point:

## Applications(2)

Amplitude of a signal is modeled by RiceDistribution. Find the probability that the amplitude will exceed its mean value:

Evaluate numerically:

Compare the value of the MarcumQ function for large arguments to its asymptotic formula:

Construct an approximation using the central limit theorem:

Evaluate numerically: