PDF
(Built-in Mathematica Symbol) PDF[dist, x] gives the probability density function for the symbolic distribution dist evaluated at x.PDF[dist, {x_1, x_2, ...}] gives the multivariate probability density ...
ProbabilityPlot[list] generates a plot of the CDF of list against the CDF of a normal distribution.ProbabilityPlot[dist] generates a plot of the CDF of the distribution dist ...
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 ...
Series
(Built-in Mathematica Symbol) Series[f, {x, x_0, n}] generates a power series expansion for f about the point x = x_0 to order (x - x_0) n. Series[f, {x, x_0, n_x}, {y, y_0, n_y}, ...] successively finds ...
Building large software systems in Mathematica should follow the general principles that apply to building any large software system. The details may be unique to Mathematica ...
[AP91] Ascher, U. and L. Petzold. "Projected Implicit Runge–Kutta Methods for Differential Algebraic Equations." SIAM J. Numer. Anal. 28 (1991): 1097–1120. [AP98] Ascher, U. ...
The function FindClusters finds clusters in a dataset based on a distance or dissimilarity function. This package contains functions for generating cluster hierarchies and ...
EstimatedDistribution[data, dist] estimates the parametric distribution dist from data.EstimatedDistribution[data, dist, {{p, p_0}, {q, q_0}, ...}] estimates the parameters ...
Expectation[expr, x \[Distributed] dist] gives the expectation of expr under the assumption that x follows the probability distribution dist. Expectation[expr, x ...
ListLinePlot[{y_1, y_2, ...}] plots a line through a list of values, assumed to correspond to x coordinates 1, 2, .... ListLinePlot[{{x_1, y_1}, {x_2, y_2}, ...}] plots a ...