calculate.maxK: The main function for TopKInference
In TopKLists: Inference, Aggregation and Visualization for Top-K Ranked Lists

Description Usage Arguments Value Author(s) References See Also Examples

Returns a complex object named truncated.lists containing the Idata vector (see prepare.idata), the estimated truncation index j_0=k+1 (see compute.stream) for each pair of input lists, the overall top-k estimate (see j0.multi), and other objects with necessary plotting information for the aggmap

1	calculate.maxK(lists, L, d, v, threshold)

`lists`	Data frame containing two or more columns that represent input lists of ordered objects subject to comparison
`L`	Number of input lists that are compared
`d`	The maximal distance delta between object ranks required for the estimation of j_0
`v`	The pilot sample size (tuning parameter) ν required for the estimation of j_0
`threshold`	The percentage of occurencies of an object in the top-k selection among all comparisons in order to be gray-shaded in the `aggmap` as a consolidated object

A named list of the following content:

`comparedLists`	Contains information about the overlap of all pairwise compared lists (structure for the `aggmap`)
`info`	Contains information about the list names
`grayshadedLists`	Contains information which objects in a list are consolidated (gray-shaded in the `aggmap`)
`summarytable`	Table of top-k list overlaps containing rank information, the rank sum, the order of objects as a function of the rank sum, the frequency of an object in the input lists and the frequency of an object in the truncated lists (for plotting in the `aggmap`)
`vennlists`	Contains the top-k objects for each of the input lists (for display in the Venn-diagram)
`venntable`	Contains the overlap information (for display in the Venn-table)
`v`	Selected pilot sample size (tuning parameter) ν
`Ntoplot`	Number of columns to be plotted in the `aggmap`
`Idata`	Data frame of Idata vectors (see `compute.stream`) for each pair of input lists and the associated delta's
`d`	selected delta
`threshold`	selected threshold
`threshold`	number of lists
`N`	number of items in data frame (lists)
`lists`	data frame of lists that entered the analysis
`maxK`	maximal estimate of the top-k's (for all pairwise comparisons)
`topkspace`	the final integrated list of objects as result of the CEMC algorithm applied to the maxK truncated lists

Eva Budinska <budinska@iba.muni.cz>, Michael G. Schimek <michael.schimek@medunigraz.at>

Hall, P. and Schimek, M. G. (2012). Moderate deviation-based inference for random degeneration in paired rank lists. J. Amer. Statist. Assoc., 107, 661-672.

CEMC, prepare.idata

set.seed(1234)
data(breast)
truncated.lists = calculate.maxK(breast, d=6, v=10, L=3, threshold=50)
## Not run: 
aggmap(truncated.lists)

## End(Not run)