SpecDLM-class | R Documentation |
An object of class SpecDLM
specifies a prior
in which elements that are next to each other are
are expected to be more similar than elements that
are distant for each other. DLMs are typically used to
model variation over time, but are often also appropriate
for variation over age.
The prior consists of a level term, optional trend,
seasonal, and covariates terms, and an error term.
The error term can follow a normal or t distribution.
For details, see the documentation for function
DLM
.
along
The name of the dimension that the time series (or age equivalents) extend along.
phi
Damping parameter.
phiKnown
Whether the damping parameter is known or is estimated from the data.
minPhi
Minimum value for the damping parameter.
maxPhi
Maximum value for the damping parameter.
nuAlpha
Degrees of freedom for the prior for the standard deviation for innovations in the level term.
AAlpha
Scale for the prior for the standard deviation for innovations in the level term.
omegaAlphaAMax
Maximum for the standard deviation for innovations in the level term.
nuDelta
Degrees of freedom for the prior for the standard deviation for innovations in the trend term.
ADelta
Scale for the prior for the standard deviation for innovations in the trend term.
omegaDeltaAMax
Maximum for the standard deviation for innovations in the trend term.
nSeason
Number of seasons.
nuSeason
Degrees of freedom for the prior for the standard deviation for innovations in the season term.
ASeason
Scale for the prior for the standard deviation for innovations in the season term.
omegaSeasonAMax
Maximum for the standard deviation for innovations in the season term.
formula
A formula
with response
mean
.
data
A data.frame containing covariate data.
contrastsArg
A named list, the elements which are matrices or names of contrasts functions.
AIntercept
The standard deviation for the prior for the intercept in the covariates term.
nuEtaCoef
The degrees of freedom for the prior for the coefficients in the covariates term.
AEtaCoef
The scale for the prior for the coefficients in the covariates term.
nuBeta
The degrees of freedom for the error term, if the error term has a t distribution.
nuTau
The degrees of freedom for the truncated half-t prior for the standard deviation or scale parameter for the error term.
ATau
The scale for the truncated half-t prior for the standard deviation or scale parameter for the error term.
maxTau
The maximum value for the standard deviation or scale parameter for the error term.
shape1Phi
First 'sample size' parameter in beta prior for damping parameter.
shape2Phi
Second 'sample size' parameter in beta prior for damping parameter.
In normal usage, it should not be necessary to
access, or even know about, the slots of a
SpecDLM
object. The slots are not part of
the API of the package, and may change in future.
Object of class SpecDLM
are generated
using function DLM
.
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