Implementation of Forecastable Component Analysis ('ForeCA'),
    including main algorithms and auxiliary function (summary, plotting, etc.) to
    apply 'ForeCA' to multivariate time series data. 'ForeCA' is a novel dimension
    reduction (DR) technique for temporally dependent signals. Contrary to other
    popular DR methods, such as 'PCA' or 'ICA', 'ForeCA' takes time dependency
    explicitly into account and searches for the most ''forecastable'' signal.
    The measure of forecastability is based on the Shannon entropy of the spectral
    density of the transformed signal.

Methods and tools for displaying and analysing
             univariate time series forecasts including exponential smoothing
             via state space models and automatic ARIMA modelling.

Provides geometric- and regression-based forecast
    combination methods under a unified user interface for the packages 'ForecastCombinations'
    and 'GeomComb'. Additionally, updated tools and convenience functions for data pre-processing are available in order to deal with 
    common problems in forecast combination (missingness, collinearity). For method details see Hsiao C, Wan SK (2014). <doi:10.1016/j.jeconom.2013.11.003>, Hansen BE (2007). <doi:10.1111/j.1468-0262.2007.00785.x>,
    Elliott G, Gargano A, Timmermann A (2013). <doi:10.1016/j.jeconom.2013.04.017>, 
    and Clemen RT (1989). <doi:10.1016/0169-2070(89)90012-5>.

Aim: Supports the most frequently used methods to combine forecasts. Among others: Simple average, Ordinary Least Squares, Least Absolute Deviation, Constrained Least Squares, Variance-based, Best Individual model, Complete subset regressions and Information-theoretic (information criteria based).

A web application for displaying, analysing and forecasting univariate time series. Includes basic methods such as mean, naïve, seasonal naïve and drift, as well as more complex methods such as Holt-Winters Box,G and Jenkins, G (1976) <doi:10.1111/jtsa.12194> and ARIMA Brockwell, P.J. and R.A.Davis (1991) <doi:10.1007/978-1-4419-0320-4>.