Impute Environmental Variables using Mean Values of occurrences within a certain radius

Usage

ec_impute_env_values(
  data_x,
  latitude = "decimalLatitude",
  longitude = "decimalLongitude",
  radius_km = 10,
  iter = 3
)

Arguments

data_x: this is data_x which is the output of ec_extract_env_layers
latitude: default set to "decimalLatitude"
longitude: default set to "decimalLongitude"
radius_km: radius to average the values of data points within the circle to imput the values for missing datta points
iter: number of times to iterate the imputation, e.g. 1 or 2 or 3

Value

An updated table of data_x which has imputed values for the missing env variables, condition applies that the this imputation wont work if the data points are too sparse.

Examples


data_x <- data.frame(
  scientificName = "Mexacanthina lugubris",
  decimalLongitude = c(-117, -117.8, -116.9),
  decimalLatitude = c(32.9, 33.5, 31.9),
  BO_sstmean = c(12, NA, 14),
  BO_sstmin = c(9, NA, 10),
  BO_sstmax = c(14, NA, 18)
)
radius_km <- 10
iter <- 3
data_x <- ec_impute_env_values(data_x,
  latitude = "decimalLatitude",
  longitude = "decimalLongitude",
  radius_km, iter
)
#> Imputation iteration 1
#> Imputation iteration 2
#> Imputation iteration 3