KP: Kejrival-Perron procedure of breaks number detection
In d9d6ka/RANEPA-R: Set of unit root and cointegration tests
KP R Documentation
Kejrival-Perron procedure of breaks number detection
Description
Kejrival-Perron procedure of breaks number detection
Usage
KP(y, const = FALSE, breaks = 1, criterion = "aic", trim = 0.15)
Arguments
y
An input series of interest.
const
Whether the break in constant is allowed.
breaks
Number of breaks.
criterion
Needed information criterion: aic, bic, hq or lwz.
trim
A trimming value for a possible break date bounds.
Details
The code provided is the original Ox code by Skrobotov (2018)
ported to R.
Value
The estimated optimal break point.
References
Kejriwal, Mohitosh, and Pierre Perron.
“A Sequential Procedure to Determine the Number of Breaks in Trend
with an Integrated or Stationary Noise Component:
Determination of Number of Breaks in Trend.”
Journal of Time Series Analysis 31, no. 5 (September 2010): 305–28.
https://doi.org/10.1111/j.1467-9892.2010.00666.x.
d9d6ka/RANEPA-R documentation built on May 4, 2024, 7:11 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| KP | R Documentation |
Kejrival-Perron procedure of breaks number detection
Description
Kejrival-Perron procedure of breaks number detection
Usage
KP(y, const = FALSE, breaks = 1, criterion = "aic", trim = 0.15)
Arguments
y |
An input series of interest. |
const |
Whether the break in constant is allowed. |
breaks |
Number of breaks. |
criterion |
Needed information criterion: aic, bic, hq or lwz. |
trim |
A trimming value for a possible break date bounds. |
Details
The code provided is the original Ox code by Skrobotov (2018) ported to R.
Value
The estimated optimal break point.
References
Kejriwal, Mohitosh, and Pierre Perron. “A Sequential Procedure to Determine the Number of Breaks in Trend with an Integrated or Stationary Noise Component: Determination of Number of Breaks in Trend.” Journal of Time Series Analysis 31, no. 5 (September 2010): 305–28. https://doi.org/10.1111/j.1467-9892.2010.00666.x.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.