cocoreg: The Common Components by Regression (CoCoReg) algorithm In bwrc/cocoreg-r: Extract Shared Variation in Collections of Data Sets Using Regression Models

Description

An algorithm that extracts common variation between datasets using regression.

Usage

 ```1 2``` ```cocoreg(data, cyclic = FALSE, mapping_function = mapping_lm, sample_paths = FALSE, center_data = T, scale_data = F) ```

Arguments

 `data` [1,K] list of data.frames. `cyclic` boolean, Operation mode: cyclic or non-cyclic `mapping_function` function, The function to use in mappings. See mapping_lm() for an example. `sample_paths` boolean, If FALSE all paths are computed. If TRUE a subset of paths is taken: one (random) path for each starting point. Currently implemented only for cyclic=F. `center_data` boolean, Should the data be centered? `scale_data` boolean, Should the data be scaled?

Value

A list with elements:

 `\$data:` [1,K] list of data.frames containing the joint information, organised identically to the input data. `\$mappings:` [1,K*K-K] list of functions, mappings between datasets `\$paths:` [(K-1)(K-2)!, K] list of lists, paths for each data set `\$cyclic:` input cyclic as is `\$sample_paths:` boolean, TRUE if paths have been sampled, FALSE otherwise. `\$dataid:` string, Dataset identifier string `\$method:` string, Analysis method identifier string `\$wall_time_taken:` [1,1] double, Time taken to run the analysis in seconds

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```dc <- create_syn_data_toy() ccr <- cocoreg(dc\$data) ggplot_dflst(dc\$data, ncol=1) ggplot_dflst(ccr\$data, ncol=1) ## Not run: ggplot_dclst(list(orig = dc\$data, ccr = ccr\$data)) ggplot_dclst(list(orig = dc\$data, shared = ccr\$data), legendMode = 'none') ggplot_dclst(list(orig = dc\$data, ccr = ccr\$data), legendMode = 'all') ## End(Not run) ```

bwrc/cocoreg-r documentation built on May 13, 2019, 9:09 a.m.