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Resampling 1 time series at another set of (known) irregularly spaced times

The key to accomplishing this is to clarify how you want to address selecting values between the existing points, but there are many base R functions and packages that address this problem. In general the methods fall into two categories: interpolation and smoothing. Interpolation includes piecewise linear interpolation, splines, last-observation-carried-forward, and  first-order-extrapolation, all of which yield the same values of applied only at the original independent values. Smoothing methods such as regression, loess, kriging, and kernel interpolation may not have this identity property but you don't need unique input values at each independent variable value either.

Read some Task Views, e.g.

https://cran.r-project.org/web/views/NumericalMathematics.html

https://cran.r-project.org/web/views/TimeSeries.html

https://cran.r-project.org/web/views/MissingData.html
On January 9, 2019 2:55:04 PM PST, John Hillier <J.Hillier at lboro.ac.uk> wrote: