predicLA_RF_XGBtiles: predict tiles using LA, RF, SGB

In mengluchu/APMtools: statistical air pollution mapping tools

Description

predict tiles using LA, RF, SGB

Usage

predicLA_RF_XGBtiles(
  df,
  rasstack,
  yname,
  xgbname,
  rfname,
  laname,
  ntree,
  mtry,
  nrounds = 3000,
  eta = 0.007,
  gamma = 5,
  max_depth = 6,
  xgb_alpha = 0,
  xgb_lambda = 2,
  subsample = 0.7,
  ...
)

Arguments

df	the dataframe for building the model
rasstack	rasterstack, predictors
yname	the y variable name
xgbname	output filename for xgb
rfname	output filename for rf
ntree	RF ntree, default 1000
lanme	output filename for LA

Examples

xgbname = "/data/lu01/NWA/xgb6-Jul_oaq.tif"
rfname = "/data/lu01/NWA/RF6-Juloaq.tif"
laname= "/data/lu01/NWA/LA6-Juloaq.tif"
lus = raster("/data/lu01/NWA/predictor/NLstack.grd")
lf_lo = list.files("/data/lu01/NWA/Bakfietsdata", pattern = "^.*morning.*.csv$", full.names = T)
bakfile1 = read.csv(lf_lo[1])
proj = "+proj=longlat +datum=WGS84"
df = retrieve_predictor(lus, bakfile1, c("Lon", "Lat"), proj)
predicLA_RF_XGBtiles(df, lus, "NO2", xgbname=xgbname, rfname = rfname, laname = laname )

mengluchu/APMtools documentation built on Jan. 27, 2022, 2:41 a.m.