Description Usage Arguments Details Value Author(s) References Examples

Extracts and analyzes turn points of an univariate `timeSeries`

object.

1 2 3 | ```
turns(x, ...)
turnsStats(x, doplot = TRUE)
``` |

`x` |
an univariate 'timeSeries' object of financial indices or prices. |

`...` |
optional arguments passed to the function |

`doplot` |
a logical flag, should the results be plotted? By default TRUE. |

The function `turns`

determines the number and the position of
extrema (turning points, either peaks or pits) in a regular time series.

The function `turnsStats`

calculates the quantity of information
associated to the observations in this series, according to Kendall's
information theory.

The functions are borrowed from the contributed R package `pastecs`

and made ready for working together with univariate `timeSeries`

objects. You need not to load the R package `pastecs`

, the code parts
we need here are builtin in the `timeSeries`

package.

We have renamed the function `turnpoints`

to `turns`

to
distinguish between the original function in the contributed R package
`pastecs`

and our Rmetrics function wrapper.

For further details please consult the help page from the contributed R
package `pastecs`

.

`turns`

returns an object of class `timeSeries`

.

`turnsStats`

returns an object of class `turnpoints`

with the following entries:

`data`

- The dataset to which the calculation is done.

`n`

- The number of observations.

`points`

- The value of the points in the series, after elimination
of ex-aequos.

`pos`

- The position of the points on the time scale in the series
(including ex-aequos).

`exaequos`

- Location of exaequos (1), or not (0).

`nturns`

- Total number of tunring points in the whole time series.

`firstispeak`

- Is the first turning point a peak (TRUE), or
not (FALSE).

`peaks`

- Logical vector. Location of the peaks in the time series
without ex-aequos.

`pits`

- Logical vector. Location of the pits in the time series
without ex-aequos.

`tppos`

- Position of the turning points in the initial series (with
ex-aequos).

`proba`

- Probability to find a turning point at this location.

`info`

- Quantity of information associated with this point.

Frederic Ibanez and Philippe Grosjean for code from the contributed
R package `pastecs`

and Rmetrics for the function wrapper.

Ibanez, F., 1982, Sur une nouvelle application de la theorie de l'information a la description des series chronologiques planctoniques. J. Exp. Mar. Biol. Ecol., 4, 619–632

Kendall, M.G., 1976, Time Series, 2nd ed. Charles Griffin and Co, London.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
## Load Swiss Equities Series -
SPI.RET <- LPP2005REC[, "SPI"]
head(SPI.RET)
## Cumulate and Smooth the Series -
SPI <- smoothLowess(cumulated(SPI.RET), f=0.05)
plot(SPI)
## Plot Turn Points Series -
SPI.SMOOTH <- SPI[, 2]
tP <- turns(SPI.SMOOTH)
plot(tP)
## Compute Statistics -
turnsStats(SPI.SMOOTH)
``` |

```
Loading required package: timeDate
GMT
SPI
2005-11-01 0.008414595
2005-11-02 0.002519342
2005-11-03 0.012707292
2005-11-04 -0.000702757
2005-11-07 0.006205226
2005-11-08 0.000329260
Turning points for: x
nbr observations : 377
nbr ex-aequos : 0
nbr turning points: 14 (first point is a peak)
E(p) = 250 Var(p) = 66.7 (theoretical)
point type proba info
1 28 peak 2.894020e-32 104.76862
2 34 pit 1.941760e-24 78.76891
3 55 peak 1.370106e-21 69.30620
4 58 pit 9.874935e-31 99.67600
5 85 peak 6.665581e-30 96.92111
6 88 pit 5.157541e-54 177.01743
7 130 peak 2.664544e-90 297.55964
8 163 pit 7.413829e-51 166.52811
9 178 peak 2.069038e-16 52.10189
10 184 pit 1.402003e-137 454.61666
11 271 peak 3.830644e-146 483.06391
12 286 pit 1.471670e-80 265.19679
13 337 peak 7.722581e-84 276.09288
14 355 pit 6.778577e-39 126.79421
```

timeSeries documentation built on Nov. 17, 2017, 2:23 p.m.

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