Estimates spatial spread model (first or latest occurence of event)
estimateMapSpread.Rd
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)
}