xCaltaF

Time series forecasting from a pool of different forecasting methods and models using R. Forecast combination for increasing forecast-accuracy and minimizing forecast-errors. Different types of cross validation. Demand forecasting (daily, weekly, monthly, annual). Seasonal and non-seasonal data. Professional looking ggplot charts.

As subscriber you will get your unlimited amount of forecasts upon request based on your datas and individual requirements without any limitations. Available forecasting methods: Naive (NF1 and NF2), Median, Simple Moving Averages (State Space form), Exponential Smoothing (all basic types including HW), Robust Exponential Smoothing, Complex Exponential Smoothing, GUM, ARIMA, Prophet, BATS (TBATS), Bayesian Time Series, Fuzzy Time Series and Pattern Sequence Based Forecasting (PSF).