HistogramDistribution[{x_1, x_2, ...}] represents the probability distribution corresponding to a histogram of the data values x_i.HistogramDistribution[{{x_1, y_1, ...}, ...

KirchhoffGraph[kmat] gives the graph with Kirchhoff matrix kmat.KirchhoffGraph[{v_1, v_2, ...}, kmat] gives the graph with vertices v_i and Kirchhoff matrix kmat.

ListConvolve[ker, list] forms the convolution of the kernel ker with list. ListConvolve[ker, list, k] forms the cyclic convolution in which the k\[Null]^th element of ker is ...

Root[f, k] represents the exact k\[Null]^th root of the polynomial equation f[x] == 0. Root[{f, x_0}] represents the exact root of the general equation f[x] == 0 near x = ...

Exact global optimization problems can be solved exactly using Minimize and Maximize. This computes the radius of the circle, centered at the origin, circumscribed about the ...

Numerical algorithms for constrained nonlinear optimization can be broadly categorized into gradient-based methods and direct search methods. Gradient-based methods use first ...

When fitting models to data, it is often useful to analyze how well the model fits the data and how well the fitting meets the assumptions of the model. For a number of ...

AdjacencyGraph[amat] gives the graph with adjacency matrix amat.AdjacencyGraph[{v_1, v_2, ...}, amat] gives the graph with vertices v_i and adjacency matrix amat.

LocationTest[data] tests whether the mean or median of the data is zero. LocationTest[{data_1, data_2}] tests whether the means or medians of data_1 and data_2 are ...

Mathematically, sufficient conditions for a local minimum of a smooth function are quite straightforward: x^* is a local minimum if ∇f(x^*)=0 and the Hessian ∇^2f(x^*) is ...