estimate_primary_modes_1d: For each set of rows grouped by the columns in ids, binary...

In momeara/RosettaFeatures: Tools for analyzing macromolecular feature distributions with Rosetta

Description

returns a data.frame with columns c(ids, "statistic") where "statistic" is the value of "variable" where the mode occurs in each group defined by ids.

Usage

estimate_primary_modes_1d(data, ids, variable, sample_domain = NULL,
  min_count = 20, ...)

Details

data: A data.frame with columns ids and variable

ids: A vector of strings that are the column names of data that is used to group the data to make multiple comparisons at once. See the Plyr package for details.

variable: A string for a numeric column of data where the primary mode is to be computed.

min_count: The minimum number of rows in group before the primary mode is computed. This helps over-interpreting groups with very few counts

n_pts: The resolution of "variable" in measuring the location of the mode.

sample_domain: The limits of "variable", when computing the primary mode. If it isn't specified then take the whole range of "variable" over all the data.

banddwidth_tolerance: Stop the binary search of kernel density estimation

debug: Print out convergence information in computing the primary mode, and add the column "min_kernel_adjust" to the returned data.frame of the value of the kernel bandwidth for each group.

Extra parameters are passed to the density function.

momeara/RosettaFeatures documentation built on May 23, 2019, 6:07 a.m.