KinPairSimulation_composite: Constructor for KinPairSimulation Class (composite)
In kindisperse: Simulate and Estimate Close-Kin Dispersal Kernels

Description Usage Arguments Value Examples

Constructor for KinPairSimulation Class (composite)

KinPairSimulation_composite(
  data = NULL,
  kinship = NULL,
  kerneltype = NULL,
  initsigma = NULL,
  breedsigma = NULL,
  gravsigma = NULL,
  ovisigma = NULL,
  simdims = NULL,
  lifestage = NULL,
  kernelshape = NULL,
  call = NULL,
  model = NULL
)

`data`	tibble of pairwise kin classes & distances. Ideally contains fields id1 & id2 (chr) an distance (dbl) optionally includes coords (x1, y1, x2, y2), lifestage (ls1 & ls2), kinship (chr) and sims (dbl)
`kinship`	character. Code for kinship category of simulation. one of PO, FS, HS, AV, GG, HAV, GGG, 1C, 1C1, 2C, GAV, HGAV, H1C or H2C
`kerneltype`	character. Statistical model for simulated dispersal kernel. Currently either "Gaussian", "Laplace" or "vgamma" (variance-gamma).
`initsigma`	numeric. Axial sigma of prebreeding ('juvenile') dispersal kernel (axial standard deviation).
`breedsigma`	numeric. Axial sigma of breeding dispersal kernel (axial standard deviation).
`gravsigma`	numeric. Axial sigma of post-breeding ('gravid') dispersal kernel (axial standard deviation).
`ovisigma`	numeric. Axial sigma of oviposition dispersal kernel (axial standard deviation).
`simdims`	numeric. Length of side of simulated area square.
`lifestage`	character. Simulated lifestage of sampling. Either "immature" (sampled at hatching) or "ovipositional" (sampled as an adult during oviposition - essentially one lifespan later than 'immature')
`kernelshape`	numeric. Value of shape parameter for simulated kernel if kernel requires one (e.g. vgamma kernel).
`call`	call object. Use to pass the system call that led to the generation of this class. (via sys.call)
`model`	DispersalModel - model information passed from simulation function

Returns a KinPairSimulation Class object with simtype set to 'composite' and relevant fields included.

kindata <- tibble::tibble(
  id1 = c("a", "b", "c"), id2 = c("x", "y", "z"),
  distance = c(50, 45, 65), kinship = c("1C", "1C", "1C")
)
KinPairSimulation_composite(kindata,
  kinship = "1C", kerneltype = "Gaussian",
  initsigma = 15, breedsigma = 25, gravsigma = 20, ovisigma = 10, lifestage = "immature"
)