Try guessing starting parameters for model_params and model_ndvi.

model_start(DT, id = "id", year = "yr")

Arguments

DT

filtered and scaled data.table of NDVI time series. Expects columns 'scaled' and 't' are present.

id

id column. default is 'id'. See details.

year

year column name. default is 'yr'.

Value

The input DT data.table appended with xmidS_start and xmidA_start columns. Note - we curently do not attempt to guess appropriate starting values for scalS and scalA.

Details

The id argument is used to split between sampling units. This may be a point id, polygon id, pixel id, etc. depending on your analysis. This should match the id provided to filtering functions.

See also

Other model: model_ndvi, model_params

Examples

# Load data.table library(data.table) # Read in example data ndvi <- fread(system.file("extdata", "ndvi.csv", package = "irg")) # Filter and scale NDVI time series filter_ndvi(ndvi)
#> id yr DayOfYear NDVI SummaryQA filtered winter rolled top #> 1: 1 2002 3 -1367 3 4099 4099 4099 7443.4 #> 2: 2 2002 14 -304 3 5382 5382 5382 7462.9 #> 3: 3 2002 1 374 2 3702 3702 3702 6709.8 #> 4: 4 2002 15 635 3 5180 5180 5180 7288.1 #> 5: 5 2002 9 685 2 4621 4621 4621 7645.1 #> --- #> 1261: 1 2012 353 151 2 4099 4099 4099 7443.4 #> 1262: 2 2012 356 330 2 5382 5382 5382 7462.9 #> 1263: 3 2012 356 560 2 3702 3702 3702 6709.8 #> 1264: 4 2012 356 1720 2 5180 5180 5180 7288.1 #> 1265: 5 2012 356 2689 2 4621 4621 4621 7645.1
scale_doy(ndvi)
#> id yr DayOfYear NDVI SummaryQA filtered winter rolled top #> 1: 1 2002 3 -1367 3 4099 4099 4099 7443.4 #> 2: 2 2002 14 -304 3 5382 5382 5382 7462.9 #> 3: 3 2002 1 374 2 3702 3702 3702 6709.8 #> 4: 4 2002 15 635 3 5180 5180 5180 7288.1 #> 5: 5 2002 9 685 2 4621 4621 4621 7645.1 #> --- #> 1261: 1 2012 353 151 2 4099 4099 4099 7443.4 #> 1262: 2 2012 356 330 2 5382 5382 5382 7462.9 #> 1263: 3 2012 356 560 2 3702 3702 3702 6709.8 #> 1264: 4 2012 356 1720 2 5180 5180 5180 7288.1 #> 1265: 5 2012 356 2689 2 4621 4621 4621 7645.1 #> t #> 1: 0.005479452 #> 2: 0.035616438 #> 3: 0.000000000 #> 4: 0.038356164 #> 5: 0.021917808 #> --- #> 1261: 0.964383562 #> 1262: 0.972602740 #> 1263: 0.972602740 #> 1264: 0.972602740 #> 1265: 0.972602740
#> id yr DayOfYear NDVI SummaryQA filtered winter rolled top #> 1: 1 2002 3 -1367 3 4099 4099 4099 7443.4 #> 2: 2 2002 14 -304 3 5382 5382 5382 7462.9 #> 3: 3 2002 1 374 2 3702 3702 3702 6709.8 #> 4: 4 2002 15 635 3 5180 5180 5180 7288.1 #> 5: 5 2002 9 685 2 4621 4621 4621 7645.1 #> --- #> 1261: 1 2012 353 151 2 4099 4099 4099 7443.4 #> 1262: 2 2012 356 330 2 5382 5382 5382 7462.9 #> 1263: 3 2012 356 560 2 3702 3702 3702 6709.8 #> 1264: 4 2012 356 1720 2 5180 5180 5180 7288.1 #> 1265: 5 2012 356 2689 2 4621 4621 4621 7645.1 #> t scaled #> 1: 0.005479452 0 #> 2: 0.035616438 0 #> 3: 0.000000000 0 #> 4: 0.038356164 0 #> 5: 0.021917808 0 #> --- #> 1261: 0.964383562 0 #> 1262: 0.972602740 0 #> 1263: 0.972602740 0 #> 1264: 0.972602740 0 #> 1265: 0.972602740 0
# Guess starting parameters for xmidS and xmidA model_start(ndvi)
#> id yr DayOfYear NDVI SummaryQA filtered winter rolled top t #> 1: 2 2003 NA NA NA NA 5382 NA 7462.9 NA #> 2: 2 2009 NA NA NA NA 5382 NA 7462.9 NA #> 3: 2 2011 NA NA NA NA 5382 NA 7462.9 NA #> 4: 2 2011 NA NA NA NA 5382 NA 7462.9 NA #> 5: 4 2002 61 375 2 NA 5180 NA 7288.1 0.1643836 #> --- #> 1261: 5 2011 247 7634 0 7634 4621 7727 7645.1 0.6739726 #> 1262: 4 2005 251 7554 0 7554 5180 7554 7288.1 0.6849315 #> 1263: 4 2009 253 7289 0 7289 5180 7289 7288.1 0.6904110 #> 1264: 2 2008 256 7581 0 7581 5382 7581 7462.9 0.6986301 #> 1265: 5 2012 262 7773 1 7773 4621 7905 7645.1 0.7150685 #> scaled xmidS_start xmidA_start #> 1: NA 0.4767123 0.7150685 #> 2: NA 0.4575342 NA #> 3: NA 0.4986301 0.7780822 #> 4: NA 0.4986301 0.7780822 #> 5: NA 0.4328767 0.8164384 #> --- #> 1261: 1 0.4000000 0.7890411 #> 1262: 1 0.4657534 0.7534247 #> 1263: 1 0.4547945 0.7479452 #> 1264: 1 0.4712329 0.8164384 #> 1265: 1 0.3342466 NA