Evaluate to high precision:

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

Evaluate for complex arguments:

Evaluate InverseJacobiDN efficiently at high precision:

Compute average-case statistical intervals using Around:

Compute the elementwise values of an array:

Or compute the matrix InverseJacobiDN function using MatrixFunction:

Simple exact results are generated automatically:

Value at infinity:

Find a real root of the equation :

Plot InverseJacobiDN for various values of the second parameter :

Plot InverseJacobiDN as a function of its parameter :

Plot the real part of :

Plot the imaginary part of :

InverseJacobiDN is not an analytic function:

It has both singularities and discontinuities:

is injective:

InverseJacobiDN is neither non-negative nor non-positive:

InverseJacobiDN is neither convex nor concave:

First derivative:

Higher derivatives:

Plot higher derivatives for :

Differentiate InverseJacobiDN with respect to the second argument :

Higher derivatives:

Taylor expansion for around and :

Plot the first three approximations for around :

Series expansion for around :

InverseJacobiDN can be applied to a power series:

InverseJacobiDN is the inverse function of JacobiDN:

Compose with inverse function:

Use PowerExpand to disregard multivaluedness of the inverse function:

InverseJacobiDN threads elementwise over lists:

TraditionalForm formatting: