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autostsm

Automatic Structural Time Series Models

Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components 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/>.

Functions (25)

GDP

US GDP Seasonally Adjusted

US GDP Not Seasonally Adjusted

S&P 500

Unemployment Rate Seasonally Adjusted

Unemployment Rate Not Seasonally Adjusted

AutoSTSM

stsm_build_dates

Build the date sequence as a Date type

stsm_check_exo

Data check for input exo

stsm_check_exo_fc

Data check for input exo.fc

stsm_check_y

Data check for input y

stsm_constraints

Set the inequality constraints for estimation

stsm_detect_anomalies

Detect Anomalies

stsm_detect_breaks

Detect Structural Breaks

stsm_detect_cycle

Detect cycle from the data

stsm_detect_frequency

Detect frequency and dates from the data

stsm_detect_multiplicative

Detect if log transformation is best

stsm_detect_seasonality

Detect seasonality from the data

stsm_detect_trend

Detect trend type

stsm_estimate

Trend cycle seasonal decomposition using the Kalman filter.

stsm_forecast

Kalman Filter and Forecast

stsm_format_exo

Format exo

stsm_init_pars

Get initial parameter estimates for estimation

stsm_init_vals

Get initial values for the Kalman filter

Return a naive model prior decomposition

State space model

autostsm

Automatic Structural Time Series Models

v1.3

GPL (>= 2)

Authors

Alex Hubbard

Initial release

2021-05-01

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