Hypergeometric anomalies of paths or of co-occurring node pairs

One verb, two estimators, chosen by the class of x:

a hypergraph (net_hg)

co-occurring node pairs scored against a hypergeometric null built from the hyperdegrees; returns a table. See hypa.net_hg().

sequences (a long, wide or list input, or a model object carrying sequences; see sequence-input)

paths of a De Bruijn graph scored against the same null (HYPA); returns a net_hypa object. See hypa.default().

Each method keeps its own arguments; passing an argument that only the other method takes raises hypernets_bad_input.

Usage

hypa(x, ...)

Arguments

x

A net_hg, or sequences.

...

Arguments of the method for class(x).

Value

See the methods.

References

LaRock, T., Nanumyan, V., Scholtes, I., Casiraghi, G., Eliassi-Rad, T., and Schweitzer, F. (2020). HYPA: Efficient detection of path anomalies in time series data on networks. Proceedings of the 2020 SIAM International Conference on Data Mining, 460-468. doi:10.1137/1.9781611976236.52

Examples

seqs <- list(c("a", "b", "c", "a", "b", "c"), c("x", "b", "d", "x", "b", "d"),
             c("a", "b", "c", "a", "b", "c"), c("x", "b", "d", "x", "b", "d"))
hg_get(hypa(seqs, order = 2, min_count = 1))
#> [1] path      count     expected  ratio     p_adj     direction
#> <0 rows> (or 0-length row.names)