Agreement coefficients and related methods
These functions calculate the agreement coefficient and mean product difference (MPD), as well as their systematic and unsystematic components, from Ji and Gallo (2006). Agreement coefficients provides a useful measurement of agreement between two data sets which is bounded, symmetrical, and can be decomposed into systematic and unsystematic components; however, it assumes a linear relationship between the two data sets and treats both "truth" and "estimate" as being of equal quality, and as such may not be a useful metric in all scenarios.
ww_agreement_coefficient(data, ...) ## S3 method for class 'data.frame' ww_agreement_coefficient(data, truth, estimate, na_rm = TRUE, ...) ww_agreement_coefficient_vec(truth, estimate, na_rm = TRUE, ...) ww_systematic_agreement_coefficient(data, ...) ## S3 method for class 'data.frame' ww_systematic_agreement_coefficient(data, truth, estimate, na_rm = TRUE, ...) ww_systematic_agreement_coefficient_vec(truth, estimate, na_rm = TRUE, ...) ww_unsystematic_agreement_coefficient(data, ...) ## S3 method for class 'data.frame' ww_unsystematic_agreement_coefficient(data, truth, estimate, na_rm = TRUE, ...) ww_unsystematic_agreement_coefficient_vec(truth, estimate, na_rm = TRUE, ...) ww_unsystematic_mpd(data, ...) ## S3 method for class 'data.frame' ww_unsystematic_mpd(data, truth, estimate, na_rm = TRUE, ...) ww_unsystematic_mpd_vec(truth, estimate, na_rm = TRUE, ...) ww_systematic_mpd(data, ...) ## S3 method for class 'data.frame' ww_systematic_mpd(data, truth, estimate, na_rm = TRUE, ...) ww_systematic_mpd_vec(truth, estimate, na_rm = TRUE, ...) ww_unsystematic_rmpd(data, ...) ## S3 method for class 'data.frame' ww_unsystematic_rmpd(data, truth, estimate, na_rm = TRUE, ...) ww_unsystematic_rmpd_vec(truth, estimate, na_rm = TRUE, ...) ww_systematic_rmpd(data, ...) ## S3 method for class 'data.frame' ww_systematic_rmpd(data, truth, estimate, na_rm = TRUE, ...) ww_systematic_rmpd_vec(truth, estimate, na_rm = TRUE, ...)
data: A data.frame containing the columns specified by the truth
and estimate arguments.
...: Not currently used.
truth: The column identifier for the true results (that is numeric). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For _vec() functions, a numeric vector.
estimate: The column identifier for the predicted results (that is also numeric). As with truth this can be specified different ways but the primary method is to use an unquoted variable name. For _vec() functions, a numeric vector.
na_rm: A logical value indicating whether NA
values should be stripped before the computation proceeds.
A tibble with columns .metric, .estimator, and .estimate and 1 row of values. For grouped data frames, the number of rows returned will be the same as the number of groups. For _vec() functions, a single value (or NA).
Agreement coefficient values range from 0 to 1, with 1 indicating perfect agreement. truth and estimate must be the same length. This function is not explicitly spatial and as such can be applied to data with any number of dimensions and any coordinate reference system.
# Calculated values match Ji and Gallo 2006: x <- c(6, 8, 9, 10, 11, 14) y <- c(2, 3, 5, 5, 6, 8) ww_agreement_coefficient_vec(x, y) ww_systematic_agreement_coefficient_vec(x, y) ww_unsystematic_agreement_coefficient_vec(x, y) ww_systematic_mpd_vec(x, y) ww_unsystematic_mpd_vec(x, y) ww_systematic_rmpd_vec(x, y) ww_unsystematic_rmpd_vec(x, y) example_df <- data.frame(x = x, y = y) ww_agreement_coefficient(example_df, x, y) ww_systematic_agreement_coefficient(example_df, x, y) ww_unsystematic_agreement_coefficient(example_df, x, y) ww_systematic_mpd(example_df, x, y) ww_unsystematic_mpd(example_df, x, y) ww_systematic_rmpd(example_df, x, y) ww_unsystematic_rmpd(example_df, x, y)
Ji, L. and Gallo, K. 2006. "An Agreement Coefficient for Image Comparison." Photogrammetric Engineering & Remote Sensing 72(7), pp 823–833, doi: 10.14358/PERS.72.7.823.
Other agreement metrics: ww_willmott_d()
Other yardstick metrics: ww_global_geary_c(), ww_global_moran_i(), ww_local_geary_c(), ww_local_getis_ord_g(), ww_local_moran_i(), ww_willmott_d()
Useful links