logsum function

Compute the log-sum or inclusive value/utility

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")
)

Arguments

• coef: a numerical vector or a mlogit object, from which the coef vector is extracted,

• X: a matrix or a mlogit object from which the model.matrix is extracted,

• formula: a formula or a mlogit object from which the formula is extracted,

• data: a data.frame or a mlogit object from which the model.frame is extracted,

• type: 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,

• output: 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.

Returns

either a vector or a matrix.

Details

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.

See Also

mlogit() for the estimation of a multinomial logit model.

Author(s)

Yves Croissant