bfrl {fuzzyreg}

Fuzzy Linear Regression Using the Boskovitch Fuzzy Regression Line Method

Description

The function calculates fuzzy regression coeficients using the Boskovitch fuzzy regression line method (BFRL) developed by Tanaka et al. (1989). Specifically, the min problem is implemented in this function.

Usage

bfrl(x, y)

Arguments

x

matrix with two colums, representing one independent variable observations. The first column is related to the intercept, so it consists of ones. Missing values not allowed.

y

three column matrix of dependent variable values and the respective spread. Method assumes non-symmetric triangular fuzzy input. Missing values not allowed.

Details

The function input expects the response in form of a non-symmetric fuzzy number and the predictors as crisp numbers. The prediction returns non-symmetric triangular fuzzy numbers. The intercept is a non-symmetric triangular fuzzy number and the slope is a crisp number that is returned as a triangular fuzzy number with spreads equal to zero.

Value

Returns a fuzzylm object that includes the model coefficients, limits for data predictions from the model and the input data.

Note

Preferred use is through the fuzzylm wrapper function with argument method = "bfrl".

References

Skrabanek, P., Marek, J. and Pozdilkova, A. (2021) Boscovich Fuzzy Regression Line. Mathematics 9: 685.

See Also

fuzzylm

Examples

data(fuzzydat)
fuzzylm(y ~ x, fuzzydat$tan, "bfrl", , , "yl", "yr")