 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.

## Usage

``````ww_agreement_coefficient(data, ...)

# S3 method for 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 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 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 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 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 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 data.frame
ww_systematic_rmpd(data, truth, estimate, na_rm = TRUE, ...)

ww_systematic_rmpd_vec(truth, estimate, na_rm = TRUE, ...)``````

## Arguments

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.

## Value

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).

## Details

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.

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.