Calculate probabilities of a Decision Field Theory (DFT) with external thresholds.
apollo_dft(dft_settings, functionality)List of settings for the DFT model. It should contain the following elements.
alternatives: Named numeric vector. Names of alternatives and
their corresponding value in choiceVar.
avail: Named list of numeric vectors or scalars. Availabilities
of alternatives, one element per alternative. Names of
elements must match those in alternatives. Values
can be 0 or 1.
choiceVar: Numeric vector. Contains choices for all observations.
It will usually be a column from the database. Values
are defined in alternatives.
attrValues: A named list with as many elements as alternatives. Each element is itself a named list of vectors of the alternative attributes for each observation (usually a column from the database). All alternatives must have the same attributes (can be set to zero if not relevant).
altStart: A named list with as many elements as alternatives. Each elment can be a scalar or vector containing the starting preference value for the alternative.
attrWeights: A named list with as many elements as attributes,
or fewer. Each element is the weight of the attribute,
and can be a scalar, a vector with as many elements as
observations, or a matrix/array if random. They should
add up to one for each observation and draw (if present),
and will be re-scaled if they do not. attrWeights
and attrScalings are incompatible, and they should
not be both defined for an attribute. Default is 1 for
all attributes.
attrScalings: A named list with as many elements as attributes,
or fewer. Each element is a factor that scale the
attribute, and can be a scalar, a vector or a
matrix/array. They do not need to add up to one
for each observation. attrWeights and
attrScalings are incompatible, and they
should not be both defined for an attribute.
Default is 1 for all attributes.
procPars: A list containing the four DFT 'process parameters'
error_sd: Numeric scalar or vector. The standard deviation of the the error term in each timestep.
timesteps: Numeric scalar or vector. Number of timesteps to consider. Should be an integer bigger than 0.
phi1: Numeric scalar or vector. Sensitivity.
phi2: Numeric scalar or vector. Process parameter.
rows: Boolean vector. Consideration of rows in the likelihood calculation, FALSE to exclude. Length equal to the number of observations (nObs). Default is "all", equivalent to rep(TRUE, nObs).
componentName: Character. Name given to model component.
Character. Can take different values depending on desired output.
"estimate": Used for model estimation.
"prediction": Used for model predictions.
"validate": Used for validating input.
"zero_LL": Used for calculating null likelihood.
"shares_LL": Used for calculating likelihood with constants only.
"conditionals": Used for calculating conditionals.
"output": Used for preparing output after model estimation.
"raw": Used for debugging.
The returned object depends on the value of argument functionality as follows.
"estimate": vector/matrix/array. Returns the probabilities for the chosen alternative for each observation.
"prediction": List of vectors/matrices/arrays. Returns a list with the probabilities for all alternatives, with an extra element for the chosen alternative probability.
"validate": Same as "estimate"
"zero_LL": vector/matrix/array. Returns the probability of the chosen alternative when all parameters are zero.
"shares_LL": Not implemented. Returns a vector of NA with as many elements as observations.
"conditionals": Same as "estimate"
"output": Same as "estimate" but also writes summary of input data to internal Apollo log.
"raw": Same as "prediction"
Hancock, T.; Hess, S. and Choudhury, C. (2018) Decision field theory: Improvements to current methodology and comparisons with standard choice modelling techniques. Transportation Research 107B, 18 - 40. Hancock, T.; Hess, S. and Choudhury, C. (Submitted) An accumulation of preference: two alternative dynamic models for understanding transport choices. Roe, R.; Busemeyer, J. and Townsend, J. (2001) Multialternative decision field theory: A dynamic connectionist model of decision making. Psychological Review 108, 370