ModelMultinomialLogit: A light weight implementation of 'mlogit"s mlogit model.

In dymium-org/dymiumModel: Extra model classes that are compatible with dymiumCore

Description

A multinomial logit model using mlogit's formula and data structure.

Super classes

dymiumCore::Generic -> dymiumCore::Model -> dymiumModel::ModelBase -> ModelMultinomialLogit

Methods

Public methods

• ModelMultinomialLogit$new()

• ModelMultinomialLogit$predict()

• ModelMultinomialLogit$clone()

Inherited methods

• dymiumCore::Generic$debug()

• dymiumCore::Generic$is_dymium_class()

• dymiumCore::Generic$log()

• dymiumCore::Model$class()

• dymiumCore::Model$get()

• dymiumCore::Model$modify()

• dymiumCore::Model$set()

• dymiumCore::Model$simulate()

• dymiumModel::ModelBase$print()

• dymiumModel::ModelBase$summary()

---

Method new()

Initialisation function

Usage

ModelMultinomialLogit$new(params, formula, preprocessing_fn = NULL)

Arguments

params

a named numeric vector.

formula

a formula object of class mlogit::mFormula(), Formula::Formula, or formula.

preprocessing_fn

a pre-processing function that gets applied to the data given to the predict method before making the prediction.

Returns

NULL

---

Method predict()

This predict method returns probabilities generated from the parameters of this Model object.

Usage

ModelMultinomialLogit$predict(newdata, chooser_id_col, choice_id_col)

Arguments

newdata

(data.frame())
new data to generate probabilities conditioned on its explanatory variables.

chooser_id_col

(character(1))
column name of the chooser id

choice_id_col

(character(1))
column name of the choice id

Returns

a data.frame object with three columns: chooser_id (integer()), choice_id (integer()), linear_comb (numeric()), prob (numeric()). Note that, 'linear_comb' stands for linear combination (i.e. $$B1 * x1 + B2 * x2$$).

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ModelMultinomialLogit$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (requireNamespace('mlogit')) {
 data("Fishing", package = "mlogit")
 .data_dfidx <- dfidx::dfidx(Fishing, varying = 2:9, shape = "wide", choice = "mode")
 mod <- mlogit::mlogit(mode ~ price + catch, data = .data_dfidx)
 Mod <- ModelMultinomialLogit$new(params = mod$coefficients, formula = mod$formula)
}

dymium-org/dymiumModel documentation built on June 23, 2020, 11:01 a.m.