Create Time Series

## Usage

series(object, time, calendar, ...)

series(object, time, names = NULL)

# S4 method for array,numeric,TimeScale
series(object, time, calendar, scale = 1, names = NULL)

# S4 method for matrix,numeric,TimeScale
series(object, time, calendar, scale = 1, names = NULL)

series(object, time, names = NULL)

# S4 method for numeric,numeric,TimeScale
series(object, time, calendar, scale = 1, names = NULL)

series(object, time, names = NULL)

# S4 method for data.frame,numeric,TimeScale
series(object, time, calendar, scale = 1, names = NULL)

series(object, time, names = NULL)

## Arguments

object

A numeric vector, matrix or array of the observed time-series values. A data.frame will be coerced to a numeric matrix via data.matrix().

time

A numeric vector of (decimal) years or a RataDie object (see fixed()).

calendar

A TimeScale object specifying the calendar of time (see calendar()). If missing, time must be a RataDie object.

...

Currently not used.

names

A character string specifying the names of the time series.

scale

A length-one numeric vector specifying the number of years represented by one unit. It should be a power of 10 (i.e. 1000 means ka).

## Value

A TimeSeries object.

## Details

Data will be sorted in chronological order.

Other time series tools: data.frame, span(), start(), time(), window()

N. Frerebeau

## Examples

## Create time-series of 20 observations

## Univariate
## Sampled every years starting from 1029 BCE
(X <- series(rnorm(30), time = 1029:1000, calendar = BCE()))
#> 30 x 1 x 1 time series observed between -376199 and -365607 r.d.

## Terminal and sampling times (returns rata die)
start(X)
#> [1] -376199
end(X)
#> [1] -365607
time(X)
#> Rata die: number of days since 01-01-01 (Gregorian).
#>  [1] -376199 -375834 -375468 -375103 -374738 -374373 -374007 -373642 -373277
#> [10] -372912 -372546 -372181 -371816 -371451 -371085 -370720 -370355 -369990
#> [19] -369624 -369259 -368894 -368529 -368163 -367798 -367433 -367068 -366702
#> [28] -366337 -365972 -365607
span(X)
#> [1] 10592

## Multivariate
## Sampled every century starting from 1000 CE
(Y <- series(matrix(rnorm(90), 30, 3), time = 1000:1029, calendar = CE()))
#> 30 x 3 x 1 time series observed between 364878 and 375470 r.d.

## Terminal and sampling times (returns Gregorian Common Era years)
start(Y, calendar = CE())
#> [1] 1000
end(Y, calendar = CE())
#> [1] 1029
time(Y, calendar = CE())
#>  [1] 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014
#> [16] 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029
span(Y, calendar = CE())
#> [1] 29.99726

## Coerce to data frame
df <- as.data.frame(Y, calendar = BP())