multivtoydataset {samurais} | R Documentation |
A simulated non-stationary multidimensional time series with regime changes.
Description
A simulated non-stationary multidimensional time series with five regimes (segments). This time series is used for illustration.
Usage
multivtoydataset
Format
A data frame with 670 rows and 4 columns:
- x
The covariate variable (the sampling time for time series).
- y1
The first dimension of the time series. The latter has been generated as follows:
First regime: 100 values of standard Normally distributed random numbers.
Second regime: 120 values of Normally distributed random numbers with mean 7 and unit variance.
Third regime: 200 values of Normally distributed random numbers with mean 4 and unit variance.
Fourth regime: 100 values of Normally distributed random numbers with mean -1 and unit variance.
Fifth regime: 150 values of Normally distributed random numbers with mean 3.5 and unit variance.
- y2
The second dimension of the time series. The latter has been generated as follows:
First regime: 100 values of Normally distributed random numbers with mean 1 and unit variance.
Second regime: 120 values of Normally distributed random numbers with mean 5 and unit variance.
Third regime: 200 values of Normally distributed random numbers with mean 6 and unit variance.
Fourth regime: 100 values of Normally distributed random numbers with mean -2 and unit variance.
Fifth regime: 150 values of Normally distributed random numbers with mean 2 and unit variance.
- y3
The third dimension of the time series. The latter has been generated as follows:
First regime: 100 values of Normally distributed random numbers with mean -2 and unit variance.
Second regime: 120 values of Normally distributed random numbers with mean 10 and unit variance.
Third regime: 200 values of Normally distributed random numbers with mean 8 and unit variance.
Fourth regime: 100 values of Normally distributed random numbers and unit variance.
Fifth regime: 150 values of Normally distributed random numbers with mean 5 and unit variance.