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.