`ts_examples.Rd`

Example Functions, Generated by ts_. `ts_prcomp`

calculates the principal
components of multiple time series, `ts_dygraphs`

generates an interactive
graphical visualization, `ts_forecast`

return an univariate forecast,
`ts_seas`

the seasonally adjusted series.

ts_prcomp(x, ...) ts_dygraphs(x, ...) ts_forecast(x, ...) ts_seas(x, ...)

x | ts-boxable time series, an object of class |
---|---|

... | further arguments, passed to the underlying function. For help, consider these functions, e.g., stats::prcomp. |

Usually, a ts-boxable time series, with the same class as the input. `ts_dygraphs`

draws a plot.

With the exception of `ts_prcomp`

, these functions depend on external
packages.

ts_plot( ts_scale(ts_c( Male = mdeaths, Female = fdeaths, `First principal compenent` = -ts_prcomp(ts_c(mdeaths, fdeaths))[, 1] )), title = "Deaths from lung diseases", subtitle = "Normalized values" )ts_plot(ts_c( male = mdeaths, female = fdeaths, ts_forecast(ts_c(`male (fct)` = mdeaths, `female (fct)` = fdeaths))), title = "Deaths from lung diseases", subtitle = "Exponential smoothing forecast" )ts_plot( `Raw series` = AirPassengers, `Adjusted series` = ts_seas(AirPassengers), title = "Airline passengers", subtitle = "X-13 seasonal adjustment" )