extract_elo: extract Elo ratings from elo object
In EloRating: Animal Dominance Hierarchies by Elo Rating

Description Usage Arguments Details Value Author(s) Examples

extract Elo ratings from elo object

extract_elo(
  eloobject,
  extractdate = eloobject$misc["maxDate"],
  standardize = FALSE,
  IDs = NULL,
  NA.interpolate = FALSE,
  daterange = 1
)

`eloobject`	result from `elo.seq`
`extractdate`	character, date on which Elo ratings should be obtained, defaults to the last day in the data set
`standardize`	logical, should the returned ratings be scaled between 0 and 1. Default is `FALSE`. See `scale_elo`
`IDs`	character, specify IDs for which ratings are returned. By default, returns all that were present on the date or at least on one day of the date range
`NA.interpolate`	if `FALSE` (default), the last known rating is returned, which might not be from the specified date itself (but older). If `TRUE`, ratings on days without observations are linearly interpolated between days with known ratings (i.e. dates with observed interactions)
`daterange`	if averaged ratings are desired, supply here the number of days from `extractdate - 1`. By default (`daterange = 1`), the ratings of the single `extractdate` are returned. `daterange = 2` produces average ratings from `extractdate` and the day after, and so on...

extractdate can be also a vector of dates. In this case, the IDs argument has to be either a vector of length 1 (i.e. a single individual) or a vector of the same length as extractdate. In the first case, the ratings for the same individual are returned on the dates specified in extractdate. In the second case, dates and IDs are matched, i.e. the rating of the individual on that date is returned in the same order as the dates/IDs vectors.

named (IDs) vector of (average) Elo ratings, or an unnamed vector of ratings (if length of extracte is larger than 1)

Christof Neumann

data(adv)
SEQ <- elo.seq(winner=adv$winner, loser=adv$loser, Date=adv$Date)
extract_elo(SEQ, "2010-01-30")
extract_elo(SEQ, "2010-01-30", standardize=TRUE)

# same ratings (regardless of NA.interpolate),
# since "g" was observed on both days
extract_elo(SEQ, "2010-01-29", IDs="g")
extract_elo(SEQ, "2010-01-29", IDs="g", NA.interpolate=TRUE)

extract_elo(SEQ, "2010-01-31", IDs="g")
extract_elo(SEQ, "2010-01-31", IDs="g", NA.interpolate=TRUE)

# different ratings (depending on NA.interpolate),
# since "g" was not observed that day
extract_elo(SEQ, "2010-01-30", IDs="g")
extract_elo(SEQ, "2010-01-30", IDs="g", NA.interpolate=TRUE)

extract_elo(SEQ, "2010-01-10", daterange=5)
extract_elo(SEQ, "2010-01-10", daterange=5, NA.interpolate=TRUE)

# and for multiple dates and a single IDs
dates <- sample(adv$Date, size = 10, replace = TRUE)
ids <- "b"
extract_elo(eloobject = SEQ, extractdate = dates, standardize = FALSE, IDs = ids)

# and for multiple dates and IDs
dates <- sample(adv$Date, size = 10, replace = TRUE)
ids <- sample(colnames(advpres)[2:8], size = 10, replace = TRUE)
extract_elo(eloobject = SEQ, extractdate = dates, standardize = FALSE, IDs = ids)