R/dmst.zones.R

In jpfrench81/smerc: Statistical Methods for Regional Counts

#' Determine zones for the Dynamic Minimum Spanning Tree scan test
#'
#' \code{dmst.zones} determines the zones for the Dynamic
#' Minimum Spanning Tree scan test (\code{\link{dmst.test}}).  The
#' function returns the zones, as well as the associated
#' test statistic, cases in each zone, the expected number
#' of cases in each zone, and the population in each zone.
#'
#' Every zone considered must have a total population less
#' than \code{ubpop * sum(pop)}.  Additionally, the maximum
#' intercentroid distance for the regions within a zone must
#' be no more than \code{ubd * the maximum intercentroid
#' distance across all regions}.
#' @inheritParams dmst.test
#' @inheritParams mst.all
#' @inheritParams flex.zones
#' @inherit dc.zones return
#' @author Joshua French
#' @references Assuncao, R.M., Costa, M.A., Tavares, A. and
#'   Neto, S.J.F. (2006). Fast detection of arbitrarily
#'   shaped disease clusters, Statistics in Medicine, 25,
#'   723-742.  <doi:10.1002/sim.2411>
#' @export
#' @examples
#' data(nydf)
#' data(nyw)
#' coords <- as.matrix(nydf[, c("longitude", "latitude")])
#' # find zone with max statistic starting from each individual region
#' all_zones <- dmst.zones(coords,
#'   cases = floor(nydf$cases),
#'   nydf$pop, w = nyw, ubpop = 0.25,
#'   ubd = .25, longlat = TRUE
#' )
dmst.zones <- function(coords, cases, pop, w,
                       ex = sum(cases) / sum(pop) * pop,
                       ubpop = 0.5, ubd = 1, longlat = FALSE,
                       cl = NULL, progress = TRUE) {
  # sanity checking
  arg_check_dmst_zones(
    coords = coords, cases = cases,
    pop = pop, w = w, ex = ex,
    ubpop = ubpop, ubd = ubd,
    longlat = longlat, type = "all",
    progress = progress
  )
  # setup various arguments and such
  ty <- sum(cases) # total number of cases
  # intercentroid distances
  d <- gedist(as.matrix(coords), longlat = longlat)
  # upperbound for population in zone
  max_pop <- ubpop * sum(pop)
  # find all neighbors from each starting zone within distance upperbound
  nn <- nndist(d, ubd)
  # get zones and relevant information
  out <- mst.all(
    neighbors = nn, cases = cases, pop = pop,
    w = w, ex = ex, ty = ty, max_pop = max_pop,
    type = "all", nlinks = "one", early = FALSE,
    cl = cl, progress = progress
  )
  prep.mst(out)
}

#' Return nicely formatted results from mst.all
#'
#' Return nicely formatted results from mst.all
#' @return NULL
#' @export
#' @keywords internal
prep.mst <- function(mstout) {
  nn <- lapply(mstout, getElement, name = "locids")
  loglikrat <- unlist(lapply(mstout, getElement,
    name = "loglikrat"
  ))
  cases <- unlist(lapply(mstout, getElement, name = "cases"))
  expected <- unlist(lapply(mstout, getElement,
    name = "expected"
  ))
  population <- unlist(lapply(mstout, getElement,
    name = "population"
  ))
  return(list(
    zones = nn2zones(nn),
    loglikrat = loglikrat,
    cases = cases,
    expected = expected,
    population = population
  ))
}

#' Argument checking for dmst.zones, dc.zones, and
#' mlink.zones functions
#'
#' Check the arguments of the dmst.zones, dc.zones, and
#' mlink.zones functions.
#' @return NULL
#' @noRd
arg_check_dmst_zones <- function(coords, cases, pop, w, ex,
                                 ubpop, ubd, longlat, type,
                                 progress = FALSE) {
  arg_check_coords(coords)
  N <- nrow(coords)
  arg_check_cases(cases, N)
  arg_check_pop(pop, N)
  arg_check_w(w, N)
  arg_check_ex(ex, N)
  arg_check_ubpop(ubpop)
  arg_check_ubd(ubd)
  arg_check_longlat(longlat)
  if (!is.element(type, c("maxonly", "pruned", "all"))) {
    stop("Invalid type")
  }
  if (length(progress) != 1 | !is.logical(progress)) {
    stop("progress must be a logical value")
  }
}