This section shows some of the ways that TetGenLink can be applied. To use TetGenLink it must first be loaded. Next, some random points are generated and displayed.
GeneralizedLinearModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a generalized linear model of the form g -1 (\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + ...) that ...
PieChart3D[{y_1, y_2, ...}] makes a 3D pie chart with sector angle proportional to y_1, y_2, ....PieChart3D[{..., w_i[y_i, ...], ..., w_j[y_j, ...], ...}] makes a 3D pie ...
TreeGraph[{v_1, v_2, ...}, {u_1, u_2, ...}] yields a tree where u_i is the predecessor of v_i.TreeGraph[{e_1, e_2, ...}] yields a tree with edges e_j.TreeGraph[{v_1, v_2, ...
BetaPrimeDistribution[p, q] represents a beta prime distribution with shape parameters p and q. BetaPrimeDistribution[p, q, \[Beta]] represents a generalized beta prime ...
QuantilePlot[list] generates a plot of quantiles of list against the quantiles of a normal distribution.QuantilePlot[dist] generates a plot of quantiles of the distribution ...
VarianceTest[data] tests whether the variance of the data is one. VarianceTest[{data_1, data_2}] tests whether the variances of data_1 and data_2 are ...
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.
CirculantGraph[n, j] gives the circulant graph with n vertices and jump j C_n (j).CirculantGraph[n, {j_1, j_2, ...}] gives the circulant graph with n vertices and jumps j_1, ...
CompleteGraph[n] gives the complete graph with n vertices K_n.CompleteGraph[{n_1, n_2, ..., n_k}] gives the complete k-partite graph with n_1 + n_2 + \[CenterEllipsis] + n_k ...