Check, how data gaps in the time index within a group could be dealt with.

Feature request: Dealing with data gaps about prais HOT 1 OPEN

franzmohr commented on September 15, 2024

Feature request: Dealing with data gaps

from prais.

Comments (1)

SebKrantz commented on September 15, 2024

Just saw this issue after reading your comment. collapse::fdiff(x, g = group, t = time, rho = param) deals with this if the time index is integer. Otherwise, you can use collapse::timeid(time), which creates integer steps from any numeric vector based on the greatest common divisor.

library(collapse)
head(D(wlddev[-3, ], by = ~ iso3c, t = ~ year))
#>   iso3c year D1.decade D1.PCGDP D1.LIFEEX D1.GINI    D1.ODA D1.POP
#> 1   AFG 1960        NA       NA        NA      NA        NA     NA
#> 2   AFG 1961         0       NA     0.516      NA 115310005 172437
#> 4   AFG 1963        NA       NA        NA      NA        NA     NA
#> 5   AFG 1964         0       NA     0.492      NA  58200012 201576
#> 6   AFG 1965         0       NA     0.485      NA  45919983 211539
#> 7   AFG 1966         0       NA     0.482      NA -30230011 218516
head(with(wlddev[-3, ], fdiff(LIFEEX, 1, 1, iso3c, year)))
#> [1]    NA 0.516    NA 0.492 0.485 0.482