Description: Provides a common interface to time series databases. The

real-time data). There is also a (not yet well tested) mechanism to
Copyright: 2007-2011 Bank of Canada.  2012-2017 Paul Gilbert.

Title: Deep Learning Model for Time Series Forecasting
Description: RNNs are preferred for sequential data like time series, speech, text, etc. but when dealing with long range dependencies, vanishing gradient problems account for their poor performance. LSTM and GRU are effective solutions which are nothing but RNN networks with the abilities of learning both short-term and long-term dependencies. Their structural makeup enables them to remember information for a long period without any difficulty. LSTM consists of one cell state and three gates, namely, forget gate, input gate and output gate whereas GRU comprises only two gates, namely, reset gate and update gate. This package consists of three different functions for the application of RNN, LSTM and GRU to any time series data for its forecasting. For method details see Jaiswal, R. et al. (2022). <doi:10.1007/s00521-021-06621-3>.

Title: Distance Measures for Time Series data.
Author: Usue Mori, Alexander Mendiburu, J.A. Lozano
Description: This package provides a set of commonly used distance measures for time series data. The application of these distance measures is useful to perform clustering, classification or other data mining tasks.

Title: Distance Measures for Time Series Data
Imports: zoo, xts, dtw, TSclust, KernSmooth, locpol, pdc,
Description: A set of commonly used distance measures for time series data. The application of these distance measures is useful to perform clustering, classification or other data mining tasks.

Description: A set of commonly used distance measures and some additional functions which, although initially not designed for this purpose, can be used to measure the dissimilarity between time series. These measures can be used to perform clustering, classification or other data mining tasks which require the definition of a distance measure between time series.