spGARCH: spGARCH - Package to fit spatial ARCH models
In spGARCH: Spatial ARCH and GARCH Models (spGARCH)
Description
Author(s)
References
Description
A collection of functions for simulating and fitting spatial autoregressive conditional heteroscedasticity (spARCH) processes are provided.
The functions sim.spARCH and sim.spGARCH are the main function for simulating spARCH and spGARCH processes, respectively. Via the argument type several types of spatial ARCH and GARCH can be simulated, e.g., exponential spARCH models, spARCH for oriented processes, or spARCH processes with truncated error support. For details, refer the paper Otto, Schmid, and Garthoff (2018) published in Spatial Statistics.
Moreover, the package provides function for fitting spARCH models. Basically, there are two functions to fit these kind of model: qml.spARCH and qml.SARspARCH. First, spARCH models can be fitted by qml.spARCH.
Author(s)
Philipp Otto potto@europa-uni.de
References
Philipp Otto, Wolfgang Schmid, Robert Garthoff (2018). Generalised Spatial and Spatiotemporal Autoregressive Conditional Heteroscedasticity. Spatial Statistics 26, pp. 125-145.
spGARCH documentation built on Sept. 2, 2020, 9:07 a.m.
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Description Author(s) References
Description
A collection of functions for simulating and fitting spatial autoregressive conditional heteroscedasticity (spARCH) processes are provided.
The functions sim.spARCH and sim.spGARCH are the main function for simulating spARCH and spGARCH processes, respectively. Via the argument type several types of spatial ARCH and GARCH can be simulated, e.g., exponential spARCH models, spARCH for oriented processes, or spARCH processes with truncated error support. For details, refer the paper Otto, Schmid, and Garthoff (2018) published in Spatial Statistics.
Moreover, the package provides function for fitting spARCH models. Basically, there are two functions to fit these kind of model: qml.spARCH and qml.SARspARCH. First, spARCH models can be fitted by qml.spARCH.
Author(s)
Philipp Otto potto@europa-uni.de
References
Philipp Otto, Wolfgang Schmid, Robert Garthoff (2018). Generalised Spatial and Spatiotemporal Autoregressive Conditional Heteroscedasticity. Spatial Statistics 26, pp. 125-145.
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.
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