hh_durations_model.jl

const HHYMO = DataFrame(CSV.File("$PACKAGE_FOLDER/network-data/Timeuse/HH/HHYMO.csv"))

# This function applies pre-processing to the HHYMO data file, and splits it into a namedtuple, which should be faster to index.
# In particular, we avoid having to modify any strings in the error function.

const cnst_hh = (
    # Set the underlying parameters for the intervals model
    Sparam = [60,12],
    # Set parameters for intervals sample and subpopulation size
    numsamples = 10,
    subsize = size(HHYMO)[1],
    # Swap age brackets for numbers
    swap = Dict("Y" => YOUNG, "M" => MIDDLE, "O" => OLD),
    # Total weight in survey
    Wghttotal = sum(HHYMO[:,"WGHT_PER"]),
)
function make_dat_array()
    durs = hcat(
        Int.(HHYMO[!,"YDUR"*string(cnst_hh.Sparam[2])]),
        Int.(HHYMO[!,"MDUR"*string(cnst_hh.Sparam[2])]),
        Int.(HHYMO[!,"ODUR"*string(cnst_hh.Sparam[2])]),
    )
    nums = hcat(
        Int.(HHYMO[!,"YNUM"]),
        Int.(HHYMO[!,"MNUM"]),
        Int.(HHYMO[!,"ONUM"]),
    )

    WGHT = Weights(HHYMO[!,"WGHT_PER"]./cnst_hh.Wghttotal)
    AGERESP = map(r -> cnst_hh.swap[r],HHYMO[!,"AGERESP"])
    return (;
        nums,
        durs,
        WGHT,
        AGERESP
    )
end
const dat = make_dat_array() #assign a constant data array


#error function for Normal distributions
function err_hh(p,dist)

    params = get_params(p)
    age_dists = [dist(params[i,j]...) for i in YOUNG:OLD, j in YOUNG:OLD]
    duration_subarray =  dat.durs
    num_contacts_subarray = dat.nums

    AGERESP =  dat.AGERESP 
    errsum = 0
    @inbounds for i = 1:cnst_hh.subsize
        age_sample = AGERESP[i]
        @inbounds for age_j in YOUNG:OLD #for a given age_sample loop over possible contact ages
            durs = trunc.(Int,rand(rng,age_dists[age_sample,age_j],num_contacts_subarray[i,age_j])) .% durmax
            expdur = tot_dur_sample(cnst_hh.numsamples,cnst_hh.Sparam,durs)
            errsum += (expdur/cnst_hh.numsamples - duration_subarray[i,age_j])^2 #compute total 
        end
    end
    return errsum
end