# load data
data(avhrr)
# create NDVI object, correct and model values
ndvi.list <- modelNDVI(ndvi.values=avhrr.ndvi/10000,
year.int=1995, correction="bise", method="Growth", MARGIN=2,
doParallel=FALSE, slidingperiod=40)
#plot
plot(ndvi.list[[1]])
# squared Pearson correlation coefficient
rsquare(ndvi.list[[1]])
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