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DataDrivenDiffEq.jl is a package for finding systems of equations automatically from a dataset. The methods in this package take in data and return the model which generated the data. A known model is not required as input. These methods can estimate equation-free and equation-based models for discrete, continuous differential equations or direct mappings.

This package contains simple routines for finding roots, or zeros, of scalar functions of a single real variable using floating-point math. The find_zero function provides the primary interface. The basic call is find_zero(f, x0, [M], [p]; kws...) where, typically, f is a function, x0 a starting point or bracketing interval, M is used to adjust the default algorithms used, and p can be used to pass in parameters. Bisection-like algorithms. For functions where a bracketing interval is known...

... module implements two schemes for this adaptation: h-adaptivity (routines hquadrature, hcubature, hquadrature_v, and hcubature_v) and p-adaptivity (routines pquadrature, pcubature, pquadrature_v, and pcubature_v). The h- and p-adaptive routines accept the same parameters, so you can use them interchangeably, but they have very different convergence characteristics.