Uc {metrica} | R Documentation |
Lack of Consistency (Uc)
Description
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. |
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
Value
an object of class numeric
within a list
(if tidy = FALSE) or within a
data frame
(if tidy = TRUE).
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
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)