Time Series Lab
@TimeSeriesLab1
Time Series Lab is free and advanced #timeseries #forecasting #software.
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Time Series Lab is a newly developed time series analysis and forecasting package. The Time Series Lab team consists of Dr. R. Lit, Professor S.J. Koopman, and Professor A.C. Harvey.
#xgboost is added to Time Series Lab! We are very impressed with the results of XGBoost but be aware, it is not the goto algorithm for every #timeseries problem. For example, it has a hard time beating an UCM with trend + seas + 2 cycle components in our example El-Nino dataset.
Time series modelling with time-varying components score-driven models! The non-Gaussian "equivalent" of Unobserved Components Models and the Kalman Filter. Now available in Time Series Lab 2.30. Download Time Series Lab for free from timeserieslab.com. #timeseries
Updated Time Series Lab manual online, as well as in pdf version: timeserieslab.com/manual Time Series Lab: advanced time series analysis for any type of time series.
We used Time Series Lab to forecast 'The Boat Race' between Oxford and Cambridge. Logistic regression with time-varying mean revealed a cyclical pattern in the data. Next step: adding explanatory variables like for example the weight of the crew. #forecasting #theboatrace
The Kalman filter, a powerful algorithm to find signal in noisy time series. The models in Time Series Lab are set in state space form such that Kalman filter methods can be used with an endless number of applications in all industries! What do you use the Kalman filter for?
Time Series Lab 2.1 is out! This version brings more DCS (score-driven) models. These models are extremely versatile and provide a unified framework for introducing time-varying parameters in linear and nonlinear models. More on them in future tweets! #econometrics #timeseries
Check out our new case study! Estimation of the business cycle from US #GDP data gets distorted if the #COVID period is not correctly taken into account. Treatment of the COVID effect is simple with #timeserieslab. #econtwitter #econometrics #timeseries timeserieslab.com/case-studies/b…
Did you know that you can use Time Series Lab to model complex seasonal patterns? Many #timeseries exhibit multiple seasonal patterns, like hour-of-day, day-of-week, and month-of-year. Take a look at our case studies on electricity demand and call-center timeserieslab.com/case-studies-m…
Did you know that you can use Time Series Lab for anomaly detection? Time Series Lab detects outliers and structural breaks in your data. See for example our case studies: timeserieslab.com/case-studies/n… timeserieslab.com/case-studies/e…
Time Series Lab has many pre-built time series models. On top of that, you can build your own time series model by selecting from a wide range of components. Examples are, Level, Slope, 3 seasonal components, 3 cycles, and ARMA components.
Time Series Lab is used for the analysis and forecasting of a wide range of time series including economics, finance, sports, climatology, biology, engineering, and health science. Below, Time Series Lab finds a monthly seasonal and 2 cycles in El Nino temperature data.
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