getPTLExpectedCounts: Predict Distribution of Feature-Wise Differences
In LCA: Localised Co-Dependency Analysis

Description Usage Arguments Details Value Author(s)

Predicts the expected number of features with a difference between two objects of a given global dissimilarity lying within a set of specified ranges.

1	getPTLExpectedCounts(alpha,beta,gamma,bin_limits,ntrials)

`alpha`	Numeric value specifying the parameter `alpha` in the PTL model used to estimate distribution of differences between the given objects
`beta`	Numeric value specifying the parameter `beta` in the PTL model used to estimate distribution of differences between the given objects
`gamma`	Numeric value specifying the parameter `gamma` in the PTL model used to estimate distribution of differences between the given objects
`bin_limits`	Numeric vector specifying the limits of each range to be evaluated. Effectively, this gives the breakpoints between cells of the predicted histogram.
`ntrials`	Numeric value specifying the number of features being evaluated in the dataset

Uses a PTL model with the specified parameters to estimate the expected number of features with differences between specified ranges. Used in calibration of PTL model parameter prediction to the dataset.

Numeric vector giving expected counts for numbers of features with a difference lying within the given set of specified ranges.

Ed Curry e.curry@imperial.ac.uk

LCA documentation built on May 2, 2019, 8:26 a.m.