Estimates spatial spread model (first or latest occurence of event)

Estimates spatial spread model (first or latest occurence of event)

Usage

estimateMapSpread(
  data,
  Longitude,
  Latitude,
  DateOne,
  DateTwo,
  center = c("Europe", "Pacific"),
  burnin = 500,
  iter = 2000,
  nChains = 1,
  K = 50,
  MinMax = "Max",
  DateType = "Interval",
  dateUnc = "mid point",
  CoordType = "decimal degrees",
  smoothConst = 1,
  penalty = 1,
  splineType = 2,
  shinyApp = FALSE,
  outlier = FALSE,
  outlierValue = 4,
  outlierD = FALSE,
  outlierValueD = 4,
  restriction = c(-90, 90, -180, 180),
  correctionPac = FALSE,
  thinning = 2,
  spreadQ = 0.01,
  minValue = -Inf
)

Arguments

data

data.frame: data

Longitude

character: name of longitude variable

Latitude

character: name of latitude variable

DateOne

character: name of date variable 1 (lower interval point / mean / single point)

DateTwo

character: name of date variable 2 (upper interval point / sd / )

center

(character) center to shift data to, either "Europe" or "Pacific"

burnin

integer: number of burn-in iterations for Bayesian model (default = 500)

iter

integer: number of iterations for Bayesian model (default = 2000)

nChains

integer: number of chains for Bayesian model (default = 1)

K

integer: number of basis functions for tprs (thin plate regression spline)

MinMax

character: estimate minimum or maximum of distribution. choices: "Max", "Min"

DateType

character: one of "Interval", "Mean + 1 SD uncertainty" and "Single Point"

dateUnc

character: one of "uniform", "normal", "point"

CoordType

character: type of longitude/latitude coordinates. One of "decimal degrees", "degrees minutes seconds" and "degrees decimal minutes"

smoothConst

numeric: adjust smoothing parameter for Bayesian model (optional)

penalty

numeric: 1 for constant extrapolation, 2 for linear extrapolation

splineType

numeric: 1 for classical tprs, 2 for spherical spline

shinyApp

boolean: If called inside shinyApp: Set to true

outlier

boolean: outlier removal TRUE/FALSE

outlierValue

numeric: if outlier removal is TRUE, threshold for removals in sd

outlierD

boolean: data outlier removal TRUE/FALSE

outlierValueD

numeric: if outlierD removal is TRUE, threshold for removals in sd

restriction

numeric vector: spatially restricts model data 4 entries for latitude (min/max) and longitude(min/max)

correctionPac

boolean: correction (data augmentation) for pacific centering

thinning

numeric: mcmc thinning for bayesian models

spreadQ

numeric: exceedance quantile as buffer

minValue

numeric: minValue restriction

Examples

if (FALSE) {
# load data
data <- readRDS(system.file("extData", "exampleData.Rds", package = "DSSM"))
# estimate model-map
map <- estimateMapSpread(data = data, Longitude = "longitude",
Latitude = "latitude", DateOne = "dateLower", DateTwo = "dateUpper", iter = 200)
# Plot the map
plotMap(model = map)
}