View source: R/Proxytools_tools.R
paleodata_interpolation | R Documentation |
Interpolation functions for irregular time series
paleodata_interpolation(
xin,
interpolation_type,
interpolation_dates,
remove_na = TRUE,
aggregation = TRUE,
aggregation_fun = mean
)
xin |
Proxytibble with proxy data in 'zoo::zoo' format, or irregular time series object ('zoo::zoo'), xin can be multivariate |
interpolation_type |
Type of interpolation, either 'spline' (spline interpolation), or 'spectral' (using the interpolation method from Laepple and Huybers 2014, Rehfeld et al. 2018, implemented in 'PaleoSpec') |
interpolation_dates |
Dates of the interpolated time series |
remove_na |
Flag if NAs should be removed after the interpolation |
aggregation |
Flag if non-unique timesteps should be merged after the interpolation |
aggregation_fun |
Function for merging non-unique timesteps |
Proxytibble with interpolated proxy data in 'zoo::zoo' format or interpolated irregular time series object ('zoo::zoo')
spline (from 'stats') for spline interpolation
MakeEquidistant (from ‘PaleoSpec') for ’spectral' interpolation (optimized for computation of spectral densities from irregular time series)
# Load ice core example data
library(PTBoxProxydata)
mng <- ProxyDataManager()
icecoredata <- load_set(mng,'icecore_testset',zoo_format = 'zoo')
# Interpolate to a regular 100yr resolution between 30ka BP and 60ka BP using spline interpolation
icecoredata_interpolated <- paleodata_interpolation(icecoredata,"spline",seq(30000,60000,by=100))
# Plot datasets
plot(icecoredata_interpolated$proxy_data[[1]])
plot(icecoredata_interpolated$proxy_data[[2]])
# Interpolate to a regular 1000yr resolution between 30ka BP and 60ka BP using interpolation method from PaleoSpec package (named "spectral" because it is optimized for computation of spectral densities)
edc_data_interpolated <- paleodata_interpolation(icecoredata$proxy_data[[1]],"spectral",seq(30000,60000,by=100))
# Plot zoo data
plot(edc_data_interpolated)
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