apollo_dft {apollo}  R Documentation 
Calculate DFT probabilities
Description
Calculate probabilities of a Decision Field Theory (DFT) model and can also perform other operations based on the value of the functionality
argument.
Usage
apollo_dft(dft_settings, functionality)
Arguments
dft_settings 
List of settings for the DFT model. It should contain the following elements.

functionality 
Character. Setting instructing Apollo what processing to apply to the likelihood function. This is in general controlled by the functions that call

Value
The returned object depends on the value of argument functionality
as follows.

"components"
: Same as"estimate"

"conditionals"
: Same as"estimate"

"estimate"
: vector/matrix/array. Returns the probabilities for the chosen alternative for each observation. 
"gradient"
: Not implemented. 
"output"
: Same as"estimate"
but also writes summary of input data to internal Apollo log. 
"prediction"
: List of vectors/matrices/arrays. Returns a list with the probabilities for all alternatives, with an extra element for the chosen alternative probability. 
"preprocess"
: Returns a list with preprocessed inputs, based ondft_settings
. 
"raw"
: Same as"prediction"

"report"
: Choice overview. 
"shares_LL"
: Not implemented. Returns a vector of NA with as many elements as observations. 
"validate"
: Same as"estimate"

"zero_LL"
: vector/matrix/array. Returns the probability of the chosen alternative when all parameters are zero.
References
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