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")
)either a vector or a matrix.
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.
Yves Croissant
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.