bssm (version 2.0.2)

kfilter: Kalman Filtering

Description

Function kfilter runs the Kalman filter for the given model, and returns the filtered estimates and one-step-ahead predictions of the states \(\alpha_t\) given the data up to time \(t\).

Usage

kfilter(model, ...)
# S3 method for lineargaussian
kfilter(model, ...)
# S3 method for nongaussian
kfilter(model, ...)

Value

List containing the log-likelihood (approximate in non-Gaussian case), one-step-ahead predictions at

and filtered estimates att of states, and the corresponding variances Pt and Ptt up to the time point n+1 where n is the length of the input time series.

Arguments

model

Model of class lineargaussian, nongaussian or ssm_nlg.

...

Ignored.

Details

For non-Gaussian models, the filtering is based on the approximate Gaussian model.

See Also

bootstrap_filter

Examples

x <- cumsum(rnorm(20))
y <- x + rnorm(20, sd = 0.1)
model <- bsm_lg(y, sd_level = 1, sd_y = 0.1)
ts.plot(cbind(y, x, kfilter(model)$att), col = 1:3)