Lack of Consistency (Uc) — Uc • metrica

It estimates the Uc component from the sum of squares decomposition described by Smith & Rose (1995).

Usage

Uc(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 Uc estimates the proportion of the total sum of squares related to the lack of consistency (proportional bias) following the sum of squares decomposition suggested by Smith and Rose (1995) also known as Theil's partial inequalities. For the formula and more details, see online-documentation

References

Smith & Rose (1995). Model goodness-of-fit analysis using regression and related techniques. Ecol. Model. 77, 49–64. doi:10.1016/0304-3800(93)E0074-D

Examples

# \donttest{
set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- X + rnorm(n=100, mean = 0, sd = 3)
Uc(obs = X, pred = Y)
#> $Uc
#> [1] 2.402532
#> 
# }