TDA's conj (alternating least squares) on a preference
variable and factor columns.
Usage
tda_conj(y, x, algorithm = c("monotone", "lp"), ...)Arguments
- y
preference values.
- x
factor matrix.
- algorithm
"monotone" regression or "lp" (linear programming).
- ...
passed to
tda_run.
Examples
x <- expand.grid(a = 1:2, b = 1:2)
r <- tda_conj(y = c(4, 3, 2, 1), x = x)
cat(tail(tda_payload(r), 8), sep = "\n") # the part-worths
#> Final parameter change: 1
#> Final norm of least squares residuals: 2.22045e-16
#> Rank of design matrix: 3
#> Idx Dimension Variable Category Coefficient
#> 0 - Const - 4.0000
#> 1 1 X1 2 -1.0000
#> 2 2 X2 2 -2.0000
#> Type of equivalence: 1