RMM (version 0.1.0)

rmm: Fitting Revenue Management Models

Description

rmm is used to fit Revenue Management Models. Users can specify cl (conditional logit model) and ml (multinomial logit model) as RMM model.

Usage

rmm(rmm_data, prop = 0.7, model = "cl")

Arguments

rmm_data

an object of class "rmm_data", a output of rmm_reshape function.

prop

numeric, user assumed market share.

model

character, specify fitting method ("cl" or "ml"). "cl" (default) refers to the Conditional Logit Model, and "ml" refers to the Multinomial Logit Model.

Value

rmm returns an object of class inheriting from "rmm".

See Also

rmm fits the model with the RDE method introduced in doi:10.2139/ssrn.3598259.

Examples

# NOT RUN {
data(Hotel_Long)

# Before using the rmm function, the user must first use the rmm_shape function.
rst_reshape <- rmm_reshape(data=Hotel_Long, idvar="Booking_ID", alts="Room_Type",
                           asv="Price", resp="Purchase", min_obs=30)

# Fitting a model
rst_rmm <- rmm(rst_reshape, prop=0.7, model="cl")
print(rst_rmm)
# }