It estimates the agreement coefficient (lambda) suggested by Duveiller et al. (2016) for a continuous predicted-observed dataset.

## 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

lambda measures both accuracy and precision. It is normalized, dimensionless, bounded (-1;1), and symmetric (invariant to predicted-observed orientation). lambda is equivalent to CCC when r is greater or equal to 0. The closer to 1 the better. Values towards zero indicate low correlation between observations and predictions. Negative values would indicate a negative relationship between predicted and observed. For the formula and more details, see online-documentation

## References

Duveiller et al. (2016).
Revisiting the concept of a symmetric index of agreement for continuous datasets.
*Sci. Rep. 6, 1-14.* doi:10.1038/srep19401