Interpolation of irregular time series

This issue refers to a communicatio with Rob Hyndman started on stackoverflow.

https://stackoverflow.com/questions/61078446/interpolation-of-irregular-time-series-with-r

I'm looking for a way to interpolate irregular time series data where the timestamp is POSIXct (rather than a date).

Rob proposed following solution, which does not seem to work with the example df I created.

library(tidyverse)
library(tsibble)
library(fable)

df <- tibble(date = as.POSIXct(c("2000-01-01 00:00", "2000-01-02 01:00", "2000-01-05 00:00")),
             value = c(1,NA,2)) %>%
  as_tsibble(index = date) %>%
  fill_gaps()


df %>%
  model(naive = ARIMA(value ~ -1 + pdq(0,1,0) + PDQ(0,0,0))) %>%
  interpolate(df)

# Error in UseMethod("interpolate") : 
#  no applicable method for 'interpolate' applied to an object of class "null_mdl"
# In addition: Warning messages:
# 1: It looks like you're trying to fully specify your ARIMA model but have not said if a constant # should be included.
# You can include a constant using `ARIMA(y~1)` to the formula or exclude it by adding `ARIMA(y~0)`. 
# 2: 1 error encountered for naive
# [1] Could not find an appropriate ARIMA model.
# This is likely because automatic selection does not select models with characteristic roots that may # be numerically unstable.
# For more details, refer to https://otexts.com/fpp3/arima-r.html#plotting-the-characteristic-roots

Thanks for taking a look again!

Start by reproducing the provided R example from the Stack Overflow discussion, following the as_tsibble, fill_gaps, ARIMA, and interpolate calls. Trace why the model becomes null_mdl with POSIXct timestamps and determine whether irregular time-series interpolation is supported; done means the example works or the limitation is clearly documented.