Intersect2Mixtures

Mean1

Weight1

Mean2

Weight2

Optional, ==1 if distribution(i) is a LogNormal, default vector of zeros of length 2

IsLogDistribution

Optional, Beginning of range, where the intersect is searched for, default min(Mean1,Mean2)

MinData

Optional, End of range, where the intersect is searched for, default max(Mean1,Mean2)

MaxData

Finds the intersect of two gaussians or log gaussians

Multimodal distributions can be modelled as a mixture of components. The model is derived using the Pareto Density Estimation (PDE) for an estimation of the pdf. PDE has been designed in particular to identify groups/classes in a dataset. Precise limits for the classes can be calculated using the theorem of Bayes. Verification of the model is possible by QQ plot, Chi-squared test and Kolmogorov-Smirnov test.

Intersect2Mixtures: Intersect of two Gaussians

Description

Usage

Arguments

Value

See Also