Drivers: Time series with seasonal effect
In andrewzm/INLA: Functions which allow to perform full Bayesian analysis of latent Gaussian models using Integrated Nested Laplace Approximaxion
Description
Usage
Format
References
Examples
Description
Montly total of car drivers killed or several
injuried in England from January 1969 to December 1984
NB: The last 12 lines of the data set have the first column set to
NULL since these data where not observed but we want to predict them.
Usage
1
Format
A data frame with 204 observations on the following 4 variables.
yNumber of deaths
beltIndicator of weather the belt was compulsory to
use (1) or not (0)
trendtime (in months)
seasonaltime (in months)
References
Rue, H and Held, L. (2005)
Gaussian Markov Random Fields - Theory and Applications
Chapman and Hall
Examples
1
andrewzm/INLA documentation built on May 10, 2019, 11:12 a.m.
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Description Usage Format References Examples
Description
Montly total of car drivers killed or several injuried in England from January 1969 to December 1984
NB: The last 12 lines of the data set have the first column set to
NULL since these data where not observed but we want to predict them.
Usage
1 |
Format
A data frame with 204 observations on the following 4 variables.
yNumber of deaths
beltIndicator of weather the belt was compulsory to use (1) or not (0)
trendtime (in months)
seasonaltime (in months)
References
Rue, H and Held, L. (2005) Gaussian Markov Random Fields - Theory and Applications Chapman and Hall
Examples
1 |
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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