TEF {fuzzyreg} | R Documentation |
Total Error of Fit of Fuzzy Regression Model
Description
Calculates total error of fit of a fuzzy regression model based on the concept of difference in membership functions of triangular fuzzy numbers between the estimated and observed fuzzy dependent variables.
Usage
TEF(object, sc = 1e-06, ...)
Arguments
object |
a |
sc |
scaling constant used for numerical stability when spreads are equal to zero. |
... |
additional arguments passed to the |
Details
Calculates \sum{E}
, where E
is the difference in
membership functions between two triangular fuzzy numbers. Here, between the
observation and the prediction from a fuzzy regression model fuzzylm
.
Value
A numeric with sum of pairwise differences between the triangular fuzzy numbers.
Note
TEF
is not suitable for assessing fuzzy linear regression models that were
fitted from crisp input data. Such data will result in division by zero. The scaling
constant sc
numerically allows the calculation to proceed, but it is not
advisable. Use GOF
instead.
References
Kim B. and Bishu R. R. (1998) Evaluation of fuzzy linear regression models by comparing membership functions. Fuzzy Sets and Systems 100: 343-352.
See Also
Examples
data(fuzzydat)
f <- fuzzylm(y ~ x, fuzzydat$lee)
TEF(f)