Temporal aggregation of a Marked Process, leading to block maxima or \(r\)-largest observations.
OT2MAX(OTdata,
OTmissing = NULL,
start = NULL,
end = NULL,
MAX.r = 1L,
blockDuration = "year",
monthGapStat = TRUE,
maxMissingFrac = 0.05,
dataFrames = FALSE,
infMAX = FALSE,
plot = TRUE,
plotType = c("max", "gaps"),
jitterSeed = 123,
trace = 0L,
...)A list, the content of which depends on the value of
dataFrames. If this value is TRUE, the
following elements are returned.
A data frame of largest values by block with one row for
each observation. The largest values are given as columns
with names equal to those in the OTdata data
frame.
A data frame describing the blocks, with one row by
block. The two (POSIXct) columns "start"
and "end" provide the beginning and the end of the
block. The numeric column duration gives the
effective duration (in year) within block.
A vector with values corresponding to the days in a block (year). Each value is a estimation of the probability that the day falls in a gap.
If dataFrames is FALSE, the list still
contains probMissing as before, as well as other
lists as used in Renouv.
Vectors containing the effective duration (in years) and number of value for the blocks.
List of maxima or \(r\)-largest values for the blocks.
Summary information concerning gaps, if monthGapStat is
TRUE and if relevant information is provide via the the
OTmissing formal. The element monthGapTS is a
multivariate time series with yearly observations and one series
(column) for each of the 12 months. Each series contains the missing
fraction of the month for the considered year, ranging from
0.0 (no gap) to 1.0 (full gap). This object can be
dealt with standard methods for time-series, but the plot
method will require to select a reduced number of columns first,
see Examples.
Data frame containing a POSIXct
column date and the marks variable.
Optional data frame with columns start and end
(coerced to POSIXct) giving the beginning and the end of
gaps.
An object coerced to POSIXct indicating the beginning of
reliable/usable information. Unless this is a beginning of block
(1-st of January for years), the 1-st block will begin after
start in order to use only qualified information.
An object indicating the end of the reliable/usable
information. Unless this is a end of block (1-st of January for
years), the last block will end before end in order to
use only qualified information.
Target number of observations in the blocks. Can be of length
one (same number of observations for all blocks) or of length equal
to the number of blocks, the values being then for the blocks in the
same order. In both cases, the target number may be impossible to
reach because of a smaller number of events in the block. If
infMAX is TRUE, the target number of observations will
be reached by filling if needed with -Inf values. The
rationale for this is that a non-existing event is assumed to have
an arbitrarily small mark.
Duration of the blocks. Can only be "year" for now.
Logical. Setting it to TRUE will compute statistics
concerning the gaps and return them or show them on a plot.
Maximal fraction of a block duration (between 0 and 1) that can be
missing without leading to a NA aggregated value.
If TRUE, the result will contain data frames similar
to those found in an object with class "Rendata". If
FALSE the result will contain list and vector
objects, similar to those used as inputs in the Renouv
function under the names MAX.data and
MAX.effDuration. Note however, that -Inf values can be
found in these objects when infMAX is TRUE.
If FALSE, the target number of values the blocks will generally
not be reached, because the total number of events in a block can be
lower than the target number. Then, the target number value is revised
to the number of found values in each block. If TRUE, the
target number of values is reached by filling the values with
-Inf and the datetimes with (POSIXct) NAs.
If TRUE a simple plot is shown.
Character controlling the plot. With "max", the block maxima
are shown. With plotType = "gap", the daily and monthly gap
rates are shown. This is possible when suitable information
concerning gaps is provided in OTmissing. The plot then shows
the probability that a given day of the year falls in a gap, as well
as monthly gap rates. Most often one wants that the gap rate does
not show a seasonal behaviour. Note that gap rates for month-year
combinations are shown as grey segments after jitterizing them since
the values 0 and 1 may be observed for several
years. An alternative way to is using the monthGapTS
multivariate time series returned by the function, see
Examples.
Random seed for jittering. Used only when plot is
TRUE, plotType is "gap" and when suitable
information is provided in OTmissing.
Integer level of verbosity.
Other arguments to be passed to plot.
The data frame given in OTdata contains the events (or
arrivals) given by the date column, as well as one mark
column. Depending on the argument MAX.r, the maxima or the
\(r\)-largest observations of the marks is computed for each time
block. When known gaps exist in the data and when they are given in
OTmissing, a block for which the total duration of gaps is too
large will be omitted.