It estimates the Willmott's index of agreement (d) for a continuous predicted-observed dataset.

## Usage

d(data = NULL, obs, pred, tidy = FALSE, na.rm = TRUE)

## Arguments

data

(Optional) argument to call an existing data frame containing the data.

obs

Vector with observed values (numeric).

pred

Vector with predicted values (numeric).

tidy

Logical operator (TRUE/FALSE) to decide the type of return. TRUE returns a data.frame, FALSE returns a list; Default : FALSE.

na.rm

Logic argument to remove rows with missing values (NA). Default is na.rm = TRUE.

## Value

an object of class numeric within a list (if tidy = FALSE) or within a data frame (if tidy = TRUE).

## Details

The d index it is a normalized, dimensionless metric that tests general agreement. It measures both accuracy and precision using squared residuals. It is bounded between 0 and 1. The disadvantage is that d is an asymmetric index, that is, dependent to what is orientation of predicted and observed values. For the formula and more details, see online-documentation

## References

Willmott (1981). On the validation of models. Phys. Geogr. 2, 184–194. doi:10.1080/02723646.1981.10642213

## Examples

# \donttest{
set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- rnorm(n = 100, mean = 0, sd = 9)
d(obs = X, pred = Y)
#> \$d
#> [1] 0.3811637
#>
# }