wWHIT: Weigthed Whittaker Smoother

In kongdd/gee_whittaker: Whittaker smoother

Weigthed Whittaker Smoother

Description

Weigthed Whittaker Smoother

Usage

wWHIT(
  y,
  w,
  ylu,
  nptperyear,
  wFUN = wBisquare,
  iters = 1,
  lambda = 15,
  second = FALSE,
  ...
)

Arguments

y	Numeric vector, vegetation index time-series
w	(optional) Numeric vector, weights of y. If not specified, weights of all NA values will be wmin, the others will be 1.0.
nptperyear	Integer, number of images per year.
lambda	whittaker parameter (2-15 is suitable for 16-day VI). Multiple lambda values also are accept, then a list object return.
second	If true, in every iteration, Whittaker will be implemented twice to make sure curve fitting is smooth. If curve has been smoothed enough, it will not care about the second smooth. If no, the second one is just prepared for this situation. If lambda value has been optimized, second smoothing is unnecessary.
...	other parameters to wFUN

References

1. Eilers, P.H.C., 2003. A perfect smoother. Anal. Chem. https://doi.org/10.1021/ac034173t
   

2. Frasso, G., Eilers, P.H.C., 2015. L- and V-curves for optimal smoothing. Stat. Modelling 15, 91-111. https://doi.org/10.1177/1471082X14549288

See Also

check_input

Examples

## Not run: 
library(phenofit)
data("MOD13A1")
dt <- tidy_MOD13.gee(MOD13A1$dt)
d <- dt[site == "AT-Neu", ]

l <- check_input(d$t, d$y, d$w, nptperyear=23)
r_wWHIT <- wWHIT(l$y, l$w, l$ylu, nptperyear = 23, iters = 2)

## End(Not run)

kongdd/gee_whittaker documentation built on April 14, 2024, 5:22 a.m.