mop (version 0.1.3)

out_range: Detect values outside ranges of reference conditions

Description

Options to identify which values in a set of conditions of interest (g_matrix) are outside the range of a set of conditions of reference (m_matrix).

Usage

out_range(m_matrix, g_matrix, type = "basic")

Value

A list containing the ranges in m_matrix, results from analysis according to type, and table to help with interpretations. NA values represent conditions of interest inside ranges of reference conditions. See Details.

Arguments

m_matrix

matrix of variables representing the set of conditions to be used as reference. Each column represents a variable.

g_matrix

matrix of variables representing the set of conditions to be compared against the reference conditions (where conditions outside range are to be detected). Each column represents a variable. Variable names must match those in m_matrix.

type

character, type of identification to be performed. See Details for options.

Details

Results are produced according to type:

• basic - helps to identify conditions outside ranges, in general, one or variables are only counted as 1. This is always returned.

• simple - identifies the number of variables with conditions outside ranges, for each condition of interest outside ranges, the number of non-analogous variables is returned.

• detailed - produces various results (including the two above):

  • high_all - identifies non-analogous conditions towards high values of variables, for each variable independently.

  • low_all - identifies non-analogous conditions towards low values of variables, for each variable independently.

  • high_combined - values are used to identify combinations of variables with non-analogous conditions towards high values of the variables.

  • low_combined - values are used to identify combinations of variables with non-analogous conditions towards low values of the variables.

  • interpretation - a data.frame to help identify which variables are considered in combined results.

Examples

# data
data("reference_matrix", package = "mop")
data("matrix_of_interest", package = "mop")

# analysis
out <- out_range(m_matrix = reference_matrix,
                 g_matrix = matrix_of_interest)