Time series interpolation: monthly data to certain day frequency data-CodePudding

I have time series data containing monthly observations. I now want the given interpolate monthly values (preferred linear, cubic is fine) according to a data sequence (for eg. 15-day sequence). The intermediate goal should be to create a data frame with the date as the index and missing values for all the monthly observations.

We can consider these values starting from the start of the month, for eg. "Sep-16" indicate 2016-09-01. So we need to change the date format as well.

head(df)
#     date      sp1
# 1 Sep-16  2.58868
# 2 Oct-16  0.51014
# 3 Nov-16 -0.81165
# 4 Dec-16 -0.52575
# 5 Jan-17 -0.93884
# 6 Feb-17 -1.95657

What I want to do is to get sp1 values for the following date sequence:

DateSeq <- seq(as.Date("2016-09-01"), as.Date("2020-07-30"), by=15)

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