Quadrature / Numerical Integration of Functions.

This package implements Bayesian quadrature rules used for numerical integration of functions on a given domain. Such methods integrate a function by iteratively building a probabilistic model and adaptively choosing points to evaluate the integrand based on said model.

## Functions¶

 bayesquad(fun, input_dim[, kernel, domain, …]) Infer the solution of the uni- or multivariate integral $$\int_\Omega f(x) d \mu(x)$$ on a hyper-rectangle $$\Omega = [a_1, b_1] \times \cdots \times [a_D, b_D]$$.

## Classes¶

 BayesianQuadrature(kernel, policy) A base class for Bayesian quadrature. IntegrationMeasure(dim, domain) An abstract class for a measure against which a target function is integrated. KernelEmbedding(kernel, measure) Integrals over kernels against integration measures. GaussianMeasure(mean, cov[, dim]) Gaussian measure on Euclidean space with given mean and covariance. LebesgueMeasure(domain[, dim, normalized]) Lebesgue measure on a hyper-rectangle.