v_curve: V-curve theory to optimize Whittaker parameter 'lambda'.

In phenofit: Extract Remote Sensing Vegetation Phenology

V-curve theory to optimize Whittaker parameter lambda.

Description

V-curve is used to optimize Whittaker parameter lambda. This function is not for users!!!

Update 20180605 add weights updating to whittaker lambda selecting

Usage

v_curve(INPUT, lg_lambdas = seq(0, 5, by = 0.005), plot = FALSE, ...)

Arguments

INPUT	A list object with the elements of t, y, w, Tn (optional) and ylu, returned by check_input().
lg_lambdas	numeric vector, log10(lambda) candidates. The optimal lambda will be optimized from lg_lambda.
plot	logical. If TRUE, the optimized lambda will be printed on the console.
...	ignored.

See Also

lambda_vcurve

Examples

data("CA_NS6"); d = CA_NS6
nptperyear = 23
INPUT <- check_input(d$t, d$y, d$w, nptperyear = nptperyear,
    maxgap = nptperyear/4, alpha = 0.02, wmin = 0.2)

r <- v_curve(INPUT, lg_lambdas = seq(0, 3, 0.1), plot = TRUE)

phenofit documentation built on June 8, 2025, 9:39 p.m.