Time Series Lab

Find the signal in your time series.

Download for Windows

Time Series Lab - Score Edition v1.20

Changelog

v1.20 is the most recent version of Time Series Lab. Currently, Windows 64 bit is the only supported platform.

A few users have reported a warning message during installation. Time Series Lab - Score Edition is a new software product. It is therefore not yet recognised by Windows as a known app. Windows Defender SmartScreen, a feature that prevents unrecognized apps from running, might tell you that:

"Windows Defender Smartscreen prevented an unrecognised app from starting".

If you encounter this warning message, click the "More info" link at the end of the warning paragraph. You see a new window with a new option: Run anyway.
Of course you can always run the program by a virus scanner after which you will see that Time Series Lab - Score Edition is not malware.


Make sure to read the license agreement before installing the program.

Changelog

v1.20: 2020-06-21

  • New outline and more plot options on graph page
  • TSL manual added to docs folder in TSL install folder
  • Fixed bug that occurred when Level and AR processes were combined and Level was the init component
  • Right mouse click on text output shows additional options
  • Undo and redo added as options for text output on main page
  • Exponential link function is now the default for Poisson and Negative Binomial distribution
  • Components can now be saved as .csv as well
  • Updating of score parameter is renamed from alpha to kappa to be consistent with literature


v1.10: 2020-05-07

  • On the frontpage of the program, users can choose from pre-defined models like ARMA and GARCH models
  • Multiple lags of the score can be added to the model which gives the option to exactly replicate ARMA(p,q) and GARCH(p,q) models
  • Screenshots of the program can be taken with Ctrl+p (main monitor)
  • The Weibull distribution is added to the continuous distributions
  • Forecasts can now be saved as .csv as well
  • Loss function contributions per time period are saved together with forecasts


v1.03: 2020-03-26

  • The Generalized Gaussian, or General Error, distribution is added to the continuous distributions
  • Parameter estimates from former model run can be used as starting values even if the model changed
  • Fixed bug in standard error notation
  • For exponential link functions, leverage is incorporated in the score function
  • Initialization parameters of seasonal component can be estimated together with other hyper parameters
  • Added 1-step-ahead and multi-step-ahead forecasting on "Forecast page"


v1.01 / 1.02

  • Fixed bug in Integrated random walk calculation
  • Added additional text output in State Information section
  • Fixed bug in forecast output column headers
  • Added Autocorrelation function of scores to "Graph page"


v1.00

  • New outline of "Model setup" and "Advanced settings" menu
  • Fixed bug regarding the identification of two AR components
  • Fixed inefficiency in likelihood calculation
  • Added functionality where the user can select the time series axis from the loaded database
  • Right mouse click on graphs for additional options on "Graphics" and "Forecasting" page
  • More elaborate description of estimated model on "Main menu" page
  • Functionality added to update the program without the need of manually downloading the newest install file


v0.40

  • Diagnostic tests added
  • Interactive forecasting where losses from several loss functions are reported for user-selected forecast windows
  • Addition of probability distributions "Exponential Generalized Beta 2", "Exponential", and "Bernoulli"
  • Addition of leverage effect in scale
  • Tooltip messages are added to inform the user about functionalities


v0.30

  • Addition of second autoregressive component
  • ACF and PACF plotting functionality on "Load data" page
  • Interactive model description on "Model setup" page
  • Significance levels included in parameter report


v0.20

  • Graphical capabilities added to the "Load data" page
  • Data transformations can be applied to the data
  • Addition of explanatory variables for location and scale
  • User can select a range (t1-t2) from the time series to estimate