#autostsm 3.1.5

Minor changes

• bug fix to work with data.table >= 1.15

#autostsm 3.1.4

Minor changes

• bug fix to structural break detection with exogenous data

#autostsm 3.1.3

Minor changes

• bug fix to weekly seasonal detection

#autostsm 3.1.2

Minor changes

• using sentinel “_PACKAGE”

#autostsm 3.1.1

Major changes

updated to fix issue calculating unobserved series at time 0 when there are lags

Minor changes

• bug fixes involving exogenous inputs

#autostsm 3.1

Minor changes

• bug fixes involving exogenous inputs

#autostsm 3.0.4

Minor changes

• updated required version of kalmanfilter package

#autostsm 3.0.3

Minor changes

• updated to use the kalmanfilter package rather than have its own internal Kalman filter routine, the kalmanfilter package is actually the Kalman filter routine that was built in this package

#autostsm 3.0.2

Minor Changes

• updated Rcpp code to handle deprecation of << assignment operator

autostsm 3.0.1

Bug fixes

• setting deterministic models wrongly set other parameters to fixed
• build issues forced package to no longer depend on data.table but imports it

autostsm 3.0

Major changes

• Added ability to use exogenous data in the observation and/or state equations with options to specify what variables enter the equation for each unobserved components using R’s formula syntax

Bug fixes

• check for stationary cycle didn’t work as expected
• an error occurred when no constraints were being used
• an error occurred during seasonal detection for a specific case
• setting cycle to trig didn’t work as expected
• fixed some typos in the vignette
• updated vignette for exogenous observation and state data

autostsm 2.1

Major changes

• added structural break detection for the drift and trend selection
• added more user specified settings including setting cycle with NULL, FALSE, trig, arma with user specified arma order

Bug fixes

• arma and cycle selection didn’t work as expected

autostsm 2.0

Major changes

• Added structural interpolation models to interpolate lower frequency time series to a higher frequency (i.e quarterly to monthly)