I'm just trying to run your example code over a test case I have and I'm encountering the following error:
> # Create temporal patterns
> profiles_library <- createPatterns(training_ts, freq = 8, formula = y ~ s(x))
Error in smooth.construct.tp.smooth.spec(object, dk$data, dk$knots) :
A term has fewer unique covariate combinations than specified maximum degrees of freedom
I believe this may relate to gam, I'll be trying to add in an argument for k and see if I can lower the DoF.
What would your recommendations be in terms of frequency of time-series data, my dataset (below) is pretty sparse earlier on in the time-series. Should I interpolate some dates between Feb-June?
Some brief details on my image/sample set:
Sentinel-2 over the following dates:
2022-02-08
2022-02-18
2022-03-20
2022-04-14
2022-05-04
2022-06-08
2022-06-13
2022-06-18
2022-06-23
2022-06-28
2022-07-08
2022-07-13
2022-07-18
2022-07-28
2022-08-02
2022-08-07
With 331 sample points (some of which are over the period 2022/02/18 - 2022/06/08)
Hey,
I'm just trying to run your example code over a test case I have and I'm encountering the following error:
I believe this may relate to gam, I'll be trying to add in an argument for k and see if I can lower the DoF.
What would your recommendations be in terms of frequency of time-series data, my dataset (below) is pretty sparse earlier on in the time-series. Should I interpolate some dates between Feb-June?
Some brief details on my image/sample set: Sentinel-2 over the following dates: 2022-02-08 2022-02-18 2022-03-20 2022-04-14 2022-05-04 2022-06-08 2022-06-13 2022-06-18 2022-06-23 2022-06-28 2022-07-08 2022-07-13 2022-07-18 2022-07-28 2022-08-02 2022-08-07
With 331 sample points (some of which are over the period 2022/02/18 - 2022/06/08)