rmm | R Documentation |
rmm
is used to fit Revenue Management Models. Users can specify
cl (conditional logit model) and ml (multinomial logit model) as RMM model.
rmm(rmm_data, prop = 0.7, model = "cl")
rmm_data |
an object of class "rmm_data", a output of |
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. |
rmm
returns an object of class inheriting from "rmm".
rmm
fits the model with the RDE method introduced in doi:10.2139/ssrn.3598259.
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)
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