5, 2015 /PRNewswire/ --AWS re:Invent 2015 -- Basho Technologies, the creator and developer of Riak software, today announced Basho Riak TS, a distributed NoSQL database architected to aggregate and analyze massive amounts of sequenced, unstructured data generated from the Internet of Things (IoT) and other time series
The time-series momentum trading strategies in the Asian market are least effective and less profitable compared with the time series
momentum trading strategies defined over the two other markets.
The main objective of this activity is to develop general analytical methods for the exploitation of the information contained in Satellite Image Time Series
Tsay summarizes the basic concepts and ideas of analyzing multivariate dependent data, provides econometric and statistical models useful for describing the dynamic dependence between variables, discusses the identifiability problem when the models become too flexible, introduces ways to search for simplifying structure hidden in high-dimensional time series
, addresses the applicabilities and limitations of multivariate time series
method, and develops a software package for readers to apply the methods and models he discusses.
Through the scatter plot, we can easily find that time series
is not stable.
Fuzzy time series
is based on many antecedents and single consequent.
To ensure a high consistency of the displacements data the dam monitoring companies have to make reports that involve correlations between the two displacements time series
(Pytharouli & Stiros, 2005).
Choi and Varian (2009) show that Google Trends data can help improve their forecasts of the current level of activity for a number of different US economic time series
, including automobile, home, and retail sales, as well as travel behaviour.
As was shown in our previous works, the similarity of histograms built on the base of short samples of the time series
of fluctuations measured on the processes of different nature, changes the regularly with time.
In our study, a noise-reduction technique for uncorrelated observation noise that is based on autoregressive integrated moving average (ARIMA) time series
modeling is investigated.
clustering has attracted increasing interest in the last decade, particularly for long time series
such as those arising in the bioinformatics and financial domains.