TimeSeriesClass | R Documentation |
timeSeries
creates a "timeSeries"
object from scratch.
timeSeries(data, charvec, units = NULL, format = NULL, zone = "",
FinCenter = "", recordIDs = data.frame(), title = NULL,
documentation = NULL, ...)
data |
a |
charvec |
a character vector of dates and times or any objects which can
be coerced to a |
units |
an optional character string, which allows to overwrite the
current column names of a |
format |
the format specification of the input character vector, a character string with the format in POSIX notation. |
zone |
the time zone or financial center where the data were recorded. |
FinCenter |
a character with the the location of the financial center named as "continent/city". |
recordIDs |
for |
title |
an optional title string, if not specified the input's data name is deparsed. |
documentation |
optional documentation string, or a vector of character strings. |
... |
arguments passed to other methods. |
Generation of Time Series Objects:
We have defined a "timeSeries"
class which is in many aspects
similar to the S-Plus class with the same name, but has also some
important differences. The class has seven Slots, the 'Data' slot
which holds the time series data in matrix form, the 'position' slot
which holds the time/date as a character vector, the 'format' and
'FinCenter' slots which are the same as for the 'timeDate' object, the
'units' slot which holds the column names of the data matrix, and a
'title' and a 'documentation' slot which hold descriptive character
strings. Date and time is managed in the same way as for
timeDate
objects.
as.timeSeries
also creates "timeSeries"
objects.
as.timeSeries(x)
is mostly equivalent to timeSeries(x)
but the two functions have different methods. Beside that, the main
difference between the two functions is that as.timeSeries
doesn't accept additional arguments. The one argument call is
naturally interpreted as ‘convert to’, so
as.timeSeries
is more expressive and is recommended in
that case.
"timeSeries"
methods are provided for many base R functions,
including arithmetic operations, mathematical functions, print
,
summary
, and time series functions. Not all are explicitly
documented, since they can just be used.
an S4 object of class "timeSeries"
as.timeSeries
,
class timeSeries
,
## Load Microsoft data -
# Microsoft Data:
setRmetricsOptions(myFinCenter = "GMT")
data(MSFT)
head(MSFT)
## Create a 'timeSeries' object, the direct Way ...
Close <- MSFT[, 5]
head(Close)
## Create a 'timeSeries' object from scratch -
data <- as.matrix(MSFT[, 4])
charvec <- rownames(MSFT)
Close <- timeSeries(data, charvec, units = "Close")
head(Close)
c(start(Close), end(Close))
## Cut out April data from 2001 -
tsApril01 <- window(Close, "2001-04-01", "2001-04-30")
tsApril01
## Compute Continuous Returns -
returns(tsApril01)
## Compute Discrete Returns -
returns(tsApril01, type = "discrete")
## Compute Discrete Returns, Don't trim -
returns(tsApril01, trim = FALSE)
## Compute Discrete Returns, Use Percentage Values -
tsRet <- returns(tsApril01, percentage = TRUE, trim = FALSE)
tsRet
## Aggregate Weekly -
GoodFriday(2001)
to <- timeSequence(from = "2001-04-11", length.out = 3, by = "week")
from <- to - 6*24*3600
from
to
applySeries(tsRet, from, to, FUN = sum)
## Create large 'timeSeries' objects with different 'charvec' object classes -
# charvec is a 'timeDate' object
head(timeSeries(1:1e6L, timeSequence(length.out = 1e6L, by = "sec")))
head(timeSeries(1:1e6L, seq(Sys.timeDate(), length.out = 1e6L, by = "sec")))
# 'charvec' is a 'POSIXt' object
head(timeSeries(1:1e6L, seq(Sys.time(), length.out = 1e6L, by = "sec")))
# 'charvec' is a 'numeric' object
head(timeSeries(1:1e6L, 1:1e6L))
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