Since data_SS columns largely have a specific, required
format, the prepSS function can often automatically decipher the
data, but the user may specify explicit instructions for parsing the data
for safety if desired. If the data are formatted properly, the automatic
parsing is reliable in most cases. There are two exceptions. (1) If
there is more than one column with possible dates (formatted as formal
dates (as class Date, POSIXlt or POSIXct) or
character strings or factors that can be unambiguously interpreted as
dates (with assumed format "2018-05-15" or "2018/5/15"). In that case,
the user must specify the desired dates as dateColumn. (2) If
there is a covariate column consisting entirely of 0s and 1s. In that
case, the user must specify the column(s) in covars.
prepSS(data_SS, SSdate = NULL, preds = NULL)data frame or matrix with search schedule parameters, including columns for search dates, covariates (describing characteristics of the search intervals), and each unit (with 1s and 0s to indicate whether the given unit was searched (= 1) or not (= 0) on the given date)
name of the column with the search dates in it
(optional). If no SSdate is given, prepSS will
try to find the date column based on data formats. If there is exactly one
column that can be interpreted as dates, that column will be taken as the
dates searched. If more than one date column is found, prepSS exits
with an error message.
vector of character strings giving the names of columns to be
interpreted as potential covariates (optional). Typically, it is not
necessary for a user to provide a value for preds. It is used only
to identify specific columns of 1s and 0s as covariates rather than as
search schedules.
prepSS object that can be conveniently used in the splitting
functions.
# NOT RUN {
data(mock)
prepSS(mock$SS)
# }
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