Weights for spatial interpolation

cal_weight(
  points,
  range,
  res = 0.5,
  cdd = 450,
  m = 4,
  nstation.max = 8,
  nstation.min = 3,
  wFUN = c("wFUN_adw", "wFUN_idw", "wFUN_thiessen", "wFUN_mean"),
  .progress = "none",
  ...
)

cal_weight_sf(
  points,
  range = NULL,
  res = 0.25,
  cdd = 450,
  m = 4,
  nstation.max = 8,
  nstation.min = 3,
  wFUN = c("wFUN_adw", "wFUN_idw", "wFUN_thiessen", "wFUN_mean"),
  .progress = "none",
  ...
)

Arguments

points: A matrix (N,2) with longitude and latitude of points of data observed
range: [xmin, xmax, ymin, ymax]
res: the grid resolution (degree)
cdd: the correlation decay distance (km) for adw and searching radius for others, default (450).
m: distance weight (default 4)
nstation.max: Number of maximum stations used per point for interpolation, (default 8).
nstation.min: Number of minimum stations used per point for interpolation, (default 3).
wFUN: wFUN_* functions, see wFUN() for details
.progress: name of the progress bar to use, see create_progress_bar
...: other parameters to plyr::ldply

Value

A data.frame with longitude, latitude and interpoled points