stsm_na_kalman

Simplified version taken from the `imputeTS` package.
Uses Kalman Smoothing on structural time series models for imputation. It uses "StructTS" to build a
"basic structural model" if the frequency of y is greater than 1. Otherwise, it uses a local trend model.

Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components, plus optionality for structural interpolation, using the Kalman filter.
Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models" <doi:10.1093/oxfordhb/9780195398649.013.0006>.
Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.

Alex Hubbard

autostsm

Automatic Structural Time Series Models

stsm_na_kalman function

<dl><dt>y</dt>
<dd>Univariate time series</dd></dl>

Arguments

Missing Value Imputation by Kalman Smoothing and State Space Models — stsm_na_kalman

<dl>

<dt>y</dt>
<dd>Univariate time series</dd>

</dl>

stsm_na_kalman: Missing Value Imputation by Kalman Smoothing and State Space Models

Description

Usage

Arguments