| summary.fitted_dlm {kDGLM} | R Documentation |
Summary for a fitted kDGLM model
Description
Prints a report for a fitted_dlm object.
Usage
## S3 method for class 'fitted_dlm'
summary(
object,
t = object$t,
lag = -1,
metric.lag = 1,
metric.cutoff = floor(object$t/10),
pred.cred = 0.95,
...
)
Arguments
object |
A fitted_dlm object. |
t |
Integer: The time index for the latent states. |
lag |
Integer: The number of steps ahead used for the evaluating the latent states. Use lag<0 for the smoothed distribution, If lag==0 for the filtered distribution and lag=h for the h-step-ahead prediction. |
metric.lag |
Integer: The number of steps ahead used for the evaluating the predictions used when calculating metrics. Use metric.lag<0 for the smoothed distribution, If metric.lag==0 for the filtered distribution and metric.lag=h for the h-step-ahead prediction. |
metric.cutoff |
Integer: The cutoff time index for the metric calculation. Values before that time will be ignored. |
pred.cred |
numeric: The credibility interval to be used for the interval score. |
... |
Extra arguments passed to the coef method.#' |
Value
No return value, called to print a summary of the fitted kDGLM model.
See Also
Other auxiliary visualization functions for the fitted_dlm class:
plot.dlm_coef(),
plot.fitted_dlm(),
summary.searched_dlm()
Examples
data <- c(AirPassengers)
level <- polynomial_block(rate = 1, order = 2, D = 0.95)
season <- harmonic_block(rate = 1, order = 2, period = 12, D = 0.975)
outcome <- Poisson(lambda = "rate", data)
fitted.data <- fit_model(level, season,
AirPassengers = outcome
)
summary(fitted.data)