PElectricity1344: Electricity Prices in New England and USA
In SLBDD: Statistical Learning for Big Dependent Data
PElectricity1344 R Documentation
Electricity Prices in New England and USA
Description
Weakly series of electricity price each hour of each day during 678 weeks
in the 8 regions in New England. We have 1344 series corresponding to each
of the seven days, one of the 24 hours and for one of the regions (7x24x8=1344).
The first series correspond to the price in the first region at 1 am CT of Thursday
01/01/2004, the second to 2 am, same day and so on. Thus the first 192 series
(24 hours x 8 regions) are the price of all the hours of Thursday in the eight regions,
the next 192 are for Friday and so on. These series were used in the articles Alonso and Peña (2019),
and Peña, Tsay and Zamar (2019).
The series have been corrected of missing values at days of changing time in saving energy days.
Usage
data(PElectricity1344)
Format
An object of class "data.frame".
References
Alonso, A. M. and Peña, D. (2019). Clustering time series by linear dependency.
Statistics and Computing, 29(4):655–676.
Peña, D. Tsay, R. and Zamar, R. (2019). Empirical Dynamic Quantiles for Visualization of High-
Dimensional Time Series, Technometrics, 61:4, 429-444.
SLBDD documentation built on April 27, 2022, 5:08 p.m.
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| PElectricity1344 | R Documentation |
Electricity Prices in New England and USA
Description
Weakly series of electricity price each hour of each day during 678 weeks in the 8 regions in New England. We have 1344 series corresponding to each of the seven days, one of the 24 hours and for one of the regions (7x24x8=1344). The first series correspond to the price in the first region at 1 am CT of Thursday 01/01/2004, the second to 2 am, same day and so on. Thus the first 192 series (24 hours x 8 regions) are the price of all the hours of Thursday in the eight regions, the next 192 are for Friday and so on. These series were used in the articles Alonso and Peña (2019), and Peña, Tsay and Zamar (2019). The series have been corrected of missing values at days of changing time in saving energy days.
Usage
data(PElectricity1344)
Format
An object of class "data.frame".
References
Alonso, A. M. and Peña, D. (2019). Clustering time series by linear dependency. Statistics and Computing, 29(4):655–676.
Peña, D. Tsay, R. and Zamar, R. (2019). Empirical Dynamic Quantiles for Visualization of High- Dimensional Time Series, Technometrics, 61:4, 429-444.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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