plfit | R Documentation |
This is a wrapper around PlackettLuce
as required by
mob
for model-based recursive partitioning. It is
not intended for general use.
plfit(
y,
x = NULL,
ref = 1L,
start = NULL,
weights = NULL,
offset = NULL,
...,
estfun = FALSE,
object = FALSE
)
y |
a |
x |
unused. |
ref |
An integer or character string specifying the reference item (for
which log worth will be set to zero). If |
start |
starting values for the worth parameters and the tie parameters
on the raw scale (worth parameters need not be scaled to sum to 1). If
|
weights |
an optional vector of weights for each ranking. |
offset |
unused. |
... |
additional arguments passed to |
estfun |
logical. If |
object |
logical. If |
a list with elements
coefficients |
model coefficients. |
objfun |
the negative log-likelihood. |
estfun |
if |
object |
if |
# rankings
R <- matrix(c(1, 2, 0, 0,
4, 1, 2, 3,
2, 1, 1, 1,
1, 2, 3, 0,
2, 1, 1, 0,
1, 0, 3, 2), nrow = 6, byrow = TRUE)
colnames(R) <- c("apple", "banana", "orange", "pear")
R <- as.rankings(R)
# group rankings into two groups
G <- group(R, rep(1:2, 3))
# plfit() gives the same results as PlackettLuce()
pl <- plfit(G)
pl$coefficients
-pl$objfun
mod <- PlackettLuce(R)
coef(mod)
logLik(mod)
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