Hi all this should be a straightforward question, I just can't seem to figure it out. I would like to break up this data set biweekly in order to look at the annual cycle in 2 week intervals. I do not want to summarize or aggregate the data. I would like to do exactly what the 'week' function is doing, but every 2 weeks instead. Below is an example of the data and code. Any help would be greatly appreciated!
DF<-dput(head(indiv))
structure(list(event.id = 1142811808:1142811813, timestamp = structure(c(1323154800,
1323200450, 1323202141, 1323203545, 1323208151, 1323209966), class = c("POSIXct",
"POSIXt"), tzone = "UTC"), argos.altitude = c(43, 43, 39, 43,
44, 42), argos.best.level = c(0, -136, -128, -136, -126, -137
), argos.calcul.freq = c(0, 676813.1, 676802.4, 676813.1, 676810,
676811.8), argos.lat1 = c(43.857, 43.916, 43.87, 43.89, 43.891,
43.89), argos.lat2 = c(43.857, 35.141, 49.688, 35.254, 40.546,
54.928), argos.lc = structure(c(7L, 6L, 2L, 3L, 4L, 3L), .Label = c("0",
"1", "2", "3", "A", "B", "G", "Z"), class = "factor"), argos.lon1 = c(-77.244,
-77.326, -77.223, -77.21, -77.208, -77.21), argos.lon2 = c(-77.244,
-121.452, -46.86, -118.496, -94.12, -16.159), argos.nb.mes.identical = c(0L,
2L, 6L, 4L, 5L, 6L), argos.nopc = c(0L, 1L, 2L, 3L, 4L, 4L),
argos.sensor.1 = c(0L, 149L, 194L, 1L, 193L, 193L), argos.sensor.2 = c(0L,
220L, 216L, 1L, 216L, 212L), argos.sensor.3 = c(0L, 1L, 1L,
0L, 3L, 1L), argos.sensor.4 = c(0L, 1L, 5L, 1L, 5L, 5L),
tag.local.identifier = c(112571L, 112571L, 112571L, 112571L,
112571L, 112571L), utm.easting = c(319655.836066914, 313250.096346666,
321382.422921619, 322486.41178559, 322650.029658403, 322486.41178559
), utm.northing = c(4858437.89950188, 4865173.18448801, 4859836.18321128,
4862029.54057323, 4862136.31345349, 4862029.54057323), utm.zone = structure(c(7L,
7L, 7L, 7L, 7L, 7L), .Label = c("12N", "13N", "14N", "15N",
"16N", "17N", "18N", "19N", "20N", "22N", "39N"), class = "factor"),
study.timezone = structure(c(2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Eastern Daylight Time",
"Eastern Standard Time"), class = "factor"), study.local.timestamp = structure(c(1323154800,
1323200450, 1323202141, 1323203545, 1323208151, 1323209966
), class = c("POSIXct", "POSIXt"), tzone = "")), row.names = 1120:1125, class = "data.frame")
weeknumber<-week(timestamps(DF))