paleodata_filtering: Gaussian filtering of irregular time series (using functions...

In paleovar/ptboxproxytools: PTBox proxy tools for time series processing and analysis

Gaussian filtering of irregular time series (using functions from 'nest' package)

Description

Gaussian filtering of irregular time series (using functions from 'nest' package)

Usage

paleodata_filtering(
  xin,
  filter_type,
  filter_scales = NULL,
  detr_scale = NULL,
  smooth_scale = NULL
)

Arguments

xin	Proxytibble with proxy data in 'zoo::zoo' format, or irregular time series object ('zoo::zoo'), xin can be multivariate
filter_type	Type of filter, either 'detrend' (high pass), 'smooth' (low pass), or 'bandpass' (high and low pass)
filter_scales	Upper and lower cut-off periods for bandpass filtering
detr_scale	Cut-off period for detrending
smooth_scale	Cut-off period for smoothing

Value

Proxytibble with filtered proxy data in 'zoo::zoo' format, or filtered irregular time series object ('zoo::zoo')

See Also

gaussbandpass (from 'nest') for specifics of the Gaussian smoothing / detrending / bandpass filtering

Examples

# Load ice core example data
library(PTBoxProxydata)
mng <- ProxyDataManager()
icecoredata <- load_set(mng,'icecore_testset',zoo_format = 'zoo')
# Detrend the data with 10kyr cutoff timescale
icecoredata_detrended <- paleodata_filtering(icecoredata, 'detrend', detr_scale=10000)
# Smooth the data with 10kyr cutoff timescale
icecoredata_smoothed <- paleodata_filtering(icecoredata, 'smooth', smooth_scale=10000)
# Apply bandpass filter for timescales from 1kyr to 10kyr
icecoredata_filtered <- paleodata_filtering(icecoredata, 'bandpass', filter_scales=data.frame(lower=1000,upper=10000))
# Plot results
plot(icecoredata_detrended$proxy_data[[1]])
plot(icecoredata_smoothed$proxy_data[[1]])
plot(icecoredata_filtered$proxy_data[[1]])

paleovar/ptboxproxytools documentation built on June 9, 2025, 1:40 a.m.