flar | R Documentation |
The function calculates fuzzy regression coeficients using the fuzzy least absolute residual (FLAR) method proposed by Zeng et al. (2017) for non-symmetric triangular fuzzy numbers.
flar(x, y)
x |
matrix with the second to last columns representing independent variable observations. The first column is related to the intercept, so it consists of ones. Missing values not allowed. |
y |
matrix of dependent variable observations. The first column contains the central tendency, the second column the left spread and the third column the right spread of non-symmetric triangular fuzzy numbers. Missing values not allowed. |
The FLAR method expects real value input for the explanatory variables, and non-symmetric triangular fuzzy numbers for the response variable. The prediction returns non-symmetric triangular fuzzy numbers.
Returns a fuzzylm
object that includes the model coefficients, limits
for data predictions from the model and the input data.
Preferred use is through the fuzzylm
wrapper function with argument
method = "flar"
.
Zeng, W., Feng, Q. and Li, J. (2017) Fuzzy least absolute linear regression. Applied Soft Computing 52: 1009-1019.
fuzzylm
data(fuzzydat)
fuzzylm(y ~ x, fuzzydat$dia, "flar", , , "yl", "yl")
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