rad

Some C++ autodiff (AD) examples with binding to R through Rcpp.

Different examples have been put together showcasing AD.

Example 1

Computes the derivative of

f(x) = 3x^2 + 2x + 2

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Example 2

Computes the derivative of a function with two input variables

f(x_1, x_2) = exp(3x_1 + 4 + x_2^2)

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Example 3

Computes the derivative of the normal density, and compares the performance to the analytical solution. AD generated derivatives are about 10x slower

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Example 4

We introduce the Adept AD library and compare it to CppAD. CppAD is about twice as fast.

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Example 5

We compute the Jacobian and Hessian of a function taking a vector as input.

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Example 6

We provide a general class for defining functions and computing their derivatives. We showcase how the class can be used with R's optimisers to find the minimum of a function.

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