Mathematical operations on 'timeSeries'
methods-mathOps.Rd
Functions and methods for mathematical operations on "timeSeries"
.
Arguments
- x
an object of class
timeSeries
.
- digits
number of digits to be used in 'round' or 'signif'.
- e1, e2
-
at least one of the two objects is from class
"timeSeries"
(for the methods described on this page).
- na.rm
a logical value: should missing values be removed?
- ...
arguments to be passed.
Details
The methods for the Math
and Math2
groups of
mathematical functions return 'timeSeries' objects. Most of them work
element-wise on the data part of the time series with the exception of
cummin
, cummax
, cumsum
, and cumprod
which
work columnwise.
The Ops
group includes mathematical operators. For the binary
operators methods are defined for pairs of at least one 'timeSeries'
object. These work as expected on the data parts of the arguments.
If the operation gives a value of the same dimension as the data part
of the 'timeSeries' object, it replaces the original data in the
object.
There are also methods for quantile
and median
.
Value
the value from a mathematical or logical operation operating on
objects of class "timeSeries"
or the value computed by a
mathematical function.
Examples
## Create an Artificial 'timeSeries' Object -
setRmetricsOptions(myFinCenter = "GMT")
charvec = timeCalendar()
set.seed(4711)
data = matrix(exp(cumsum(rnorm(12, sd = 0.1))))
TS = timeSeries(data, charvec, units = "TS")
TS
#> GMT
#> TS
#> 2023-01-01 1.1995824
#> 2023-02-01 1.3757753
#> 2023-03-01 1.5506114
#> 2023-04-01 1.4887865
#> 2023-05-01 1.4005479
#> 2023-06-01 1.2043889
#> 2023-07-01 1.3069906
#> 2023-08-01 1.1867998
#> 2023-09-01 1.1815277
#> 2023-10-01 1.2389245
#> 2023-11-01 1.1230263
#> 2023-12-01 0.9596526
## Mathematical Operations: | +/- * ^ ... -
TS^2
#> GMT
#> TS
#> 2023-01-01 1.438998
#> 2023-02-01 1.892758
#> 2023-03-01 2.404396
#> 2023-04-01 2.216485
#> 2023-05-01 1.961534
#> 2023-06-01 1.450553
#> 2023-07-01 1.708224
#> 2023-08-01 1.408494
#> 2023-09-01 1.396008
#> 2023-10-01 1.534934
#> 2023-11-01 1.261188
#> 2023-12-01 0.920933
TS[2:4]
#> [1] 1.375775 1.550611 1.488787
OR = returns(TS)
OR
#> GMT
#> TS
#> 2023-02-01 0.137043950
#> 2023-03-01 0.119631824
#> 2023-04-01 -0.040687920
#> 2023-05-01 -0.061097880
#> 2023-06-01 -0.150891205
#> 2023-07-01 0.081754941
#> 2023-08-01 -0.096466789
#> 2023-09-01 -0.004452208
#> 2023-10-01 0.047435474
#> 2023-11-01 -0.098216632
#> 2023-12-01 -0.157211053
OR > 0
#> GMT
#> TS
#> 2023-02-01 TRUE
#> 2023-03-01 TRUE
#> 2023-04-01 FALSE
#> 2023-05-01 FALSE
#> 2023-06-01 FALSE
#> 2023-07-01 TRUE
#> 2023-08-01 FALSE
#> 2023-09-01 FALSE
#> 2023-10-01 TRUE
#> 2023-11-01 FALSE
#> 2023-12-01 FALSE