The logsum
function computes the inclusive value, or
inclusive utility, which is used to compute the surplus and to
estimate the two steps nested logit model.
logsum(coef, X = NULL, formula = NULL, data = NULL,
type = NULL, output = c("chid", "obs"))
a numerical vector or a mlogit
object, from which
the coef
vector is extracted,
a matrix or a mlogit
object from which the
model.matrix
is extracted,
a formula or a mlogit
object from which the
formula
is extracted,
a data.frame
or a mlogit
object from which the
model.frame
is extracted,
either "group"
or "global"
: if a
group
argument has been provided in the mlogit.data
,
the inclusive values are by default computed for every group,
otherwise, a unique global inclusive value is computed for each
choice situation,
the shape of the results: if "chid"
, the results
is a vector (if type = "global"
) or a matrix (if type =
"region"
) with row number equal to the number of choice
situation, if "obs"
a vector of length equal to the number of
lines of the data in long format is returned.
either a vector or a matrix.
The inclusive value, or inclusive utility, or log-sum is the log of
the denominator of the probabilities of the multinomial logit
model. If a "group"
variable is provided in the
"mlogit.data"
function, the denominator can either be the one
of the multinomial model or those of the lower model of the nested
logit model.
If only one argument (coef
) is provided, it should a
mlogit
object and in this case, the coefficients
and the
model.matrix
are extracted from this model.
In order to provide a different model.matrix
, further arguments
could be used. X
is a matrix
or a mlogit
from
which the model.matrix
is extracted. The
formula
-data
interface can also be used to construct the
relevant model.matrix
.
mlogit
for the estimation of a multinomial logit model.