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 ...
KernelMixtureDistribution[{x_1, x_2, ...}] represents a kernel mixture distribution based on the data values x_i.KernelMixtureDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...
Numerical algorithms for constrained nonlinear optimization can be broadly categorized into gradient-based methods and direct search methods. Gradient search methods use ...
Mathematica has over 3000 built-in functions and other objects, all based on a single unified framework, and all carefully designed to work together, both in simple ...
MixtureDistribution[{w_1, ..., w_n}, {dist_1, ..., dist_n}] represents a mixture distribution whose CDF is given as a sum of the CDFs of the component distributions dist_i, ...
TTest
(Built-in Mathematica Symbol) TTest[data] tests whether the mean of data is zero. TTest[{data_1, data_2}] tests whether the means of data_1 and data_2 are equal.TTest[dspec, \[Mu]_0] tests the mean ...
CopulaDistribution[ker, {dist_1, dist_2, ...}] represents a copula distribution with kernel distribution ker and marginal distributions dist_1, dist_2, ....
FindDistributionParameters[data, dist] finds the parameter estimates for the distribution dist from data.FindDistributionParameters[data, dist, {{p, p_0}, {q, q_0}, ...}] ...
The following are some issues and considerations to be aware of when using the Notation Package and/or designing notations. It is intrinsically difficult to debug something ...
As of Version 7.0, CovarianceMatrix has become a property of LinearModelFit.