apollo_insertFunc function

Modifies function to make it compatible with analytic gradients

Takes a likelihood function and inserts function () before key elements to allow for analytic gradient calculation

apollo_insertFunc(f, like = TRUE, randCoeff = FALSE, lcPars = FALSE)

Arguments

• f: Function. Expressions inside it will be turned into functions. Usually apollo_probabilities or apollo_randCoeff.
• like: Logical. Must be TRUE if f is apollo_probabilities. FALSE otherwise.
• randCoeff: Logical. Must be TRUE if f is apollo_randCoeff. FALSE otherwise.
• lcPars: Logical. Must be TRUE if f is apollo_lcPars. FALSE otherwise.

Returns

Function f but with relevant expressions turned into function definitions.

Details

It modifies the definition of the following models.

• ‘apollo_mnl’ : Turns all elements inside mnl_settings$V into functions.
• ‘apollo_ol’ : Turns ol_settings$V and all elements inside ol_settings$tau into functions.
• ‘apollo_op’ : Turns op_settings$V and all elements inside op_settings$tau into functions.
• ‘apollo_normalDensity’ : Turns normalDensity_settings$xNormal, normalDensity_settings$mu and normalDensity_settings$sigma into functions.

It can only track a maximum of 3 levels of depth in definitions. For example: V <- list() V[["A"]] <- b1*x1A + b2*x2A V[["B"]] <- b1*x1B + b2*x2Bmnl_settings1 <- list(alternatives=c("A", "B"), V = V, choiceVar= Y,avail = 1, componentName="MNL1") P[["MNL1"]] <-apollo_mnl(mnl_settings1, functionality)

But it may not be able to deal with the following: VA <- b1*x1A + b2*x2A V <- list() V[["A"]] <- VA V[["B"]] <- b1*x1B +b2*x2B mnl_settings1 <- list(alternatives=c("A", "B"), V = V,choiceVar= Y, avail = 1, componentName="MNL1") P[["MNL1"]] <-apollo_mnl(mnl_settings1, functionality)

But that might be enough given how apollo_dVdB works.