Full information model with Dahl's correction function

Usage

logit_correction(starts3, dat, otherdat, alts, project, expname, mod.name)

Arguments

starts3: Starting values as a vector (num). For this likelihood, the order takes: c([marginal utility from catch], [catch-function parameters], [polynomial starting parameters], [travel-distance parameters], [catch sigma]).

The number of polynomial interaction terms is currently set to 2, so given the chosen degree 'polyn' there should be (((polyn+1)*2) + 2)*(k) polynomial starting parameters, where (k) equals the number of alternatives. The marginal utility from catch and catch sigma are of length equal to unity respectively. The catch-function and travel-distance parameters are of length (# of catch variables)*(k) and (# of cost variables) respectively.
dat: Data matrix, see output from shift_sort_x, alternatives with distance.
otherdat: Other data used in model (as a list containing objects `griddat`, `intdat`, `startloc`, `polyn`, and `distance`).

For catch-function variables (`griddat`) alternative-invariant variables that are interacted with zonal constants to form the catch portion of the likelihood. Each variable name therefore corresponds to data with dimensions (number of observations) by (unity), and returns (k) parameters where (k) equals the number of alternatives. For travel-distance variables alternative-invariant variables that are interacted with travel distance to form the cost portion of the likelihood. Each variable name therefore corresponds to data with dimensions (number of observations) by (unity), and returns a single parameter. Any number of catch-function and travel-distance variables are allowed, as a list of matrices. Note the variables (each as a matrix) within `griddat` and `intdat` have no naming restrictions.

Catch-function variables may correspond to variables that affect catches across locations, or travel-distance variables may be vessel characteristics that affect how much disutility is suffered by traveling a greater distance. Note in this likelihood the catch-function variables vary across observations but not for each location: they are allowed to affect catches across locations due to the location-specific coefficients. If there are no other data, the user can set catch-function variables as ones with dimension (number of observations) by (number of alternatives) and travel-distance variables as ones with dimension (number of observations) by (unity).

The variable startloc is a matrix of dimension (number of observations) by (unity), that corresponds to the starting location when the agent decides between alternatives.

The variable polyn is a vector of length equal to unity corresponding to the chosen polynomial degree.

The variable distance is a matrix of dimension (number of observations) by (number of alternatives) corresponding to the distance to each alternative.
alts: Number of alternative choices in model as length equal to unity (as a numeric vector).
project: Name of project
expname: Expected catch table
mod.name: Name of model run for model result output table

Value

ld: negative log likelihood

Graphical examples

Figure: logit_correction_grid.png
Figure: logit_correction_travel.png
Figure: logit_correction_poly.png

Examples

if (FALSE) {
data(zi)
data(catch)
data(choice)
data(distance)
data(si)
data(startloc)

optimOpt <- c(1000,1.00000000000000e-08,1,0)

methodname <- 'BFGS'

polyn <- 3
kk <- 4

si2 <- sample(1:5,dim(si)[1],replace=TRUE)
zi2 <- sample(1:10,dim(zi)[1],replace=TRUE)

otherdat <- list(griddat=list(si=as.matrix(si),si2=as.matrix(si2)),
    intdat=list(zi=as.matrix(zi),zi2=as.matrix(zi2)),
    startloc=as.matrix(startloc),polyn=polyn,
    distance=as.matrix(distance))

initparams <- c(3, 0.5, 0.4, 0.3, 0.2, 0.55, 0.45, 0.35, 0.25,
    rep(0, (((polyn+1)*2) + 2)*kk), -0.3,-0.4, 3)

func <- logit_correction

results <- discretefish_subroutine(catch,choice,distance,otherdat,
    initparams,optimOpt,func,methodname)
}