time series

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  • noun

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a series of values of a variable at successive times

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Since the prices of any stock are based on time therefore, studying the stock prices entails studying time series data coupled with forecasting.
We hope that the results from the time series data will provide baseline information for sustaining production and for guiding agricultural policy and exports of Turkey in terms of the above-mentioned plants in forthcoming years.
The latter model captures the structure of the study time series, based on the set of other time series; thus, supporting the agricultural sector.
Apart from these random and systematic errors, site-position time series generated from continuous GPS stations reveal significant seasonal variations.
There are many ways to manage large-scale data storage and analysis; with regards to time series processing the Apache Distribution of Hadoop is the most efficient file system.
Usually the expressive method of the first-order of time series based on computer prediction is as follows:
The goals of the present study were to (1) identify common trends in zooplankton and fish density and biomass time series in Lake Chapala, and (2) elucidate the importance of water temperature, electrical conductivity, dissolved oxygen, pH, and alkalinity on these common trends.
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.
SS model is based on idea that time series will have the same gradient (slope) in the next time period like in previous.
Top Picks is a form-based application for both Industry Data and Commodity Data that allows the user to quickly obtain PPI time series data by selecting the high-level aggregate and other commonly requested time series, including the All Commodities Index and the FD-ID indexes (for example, Final Demand).
A consequence of persistence in a time series is that a new datum coming in does not bring as much new information about the statistical properties as would be the case for a time series of independent data.
Tenders are invited for: Gstp - data mining for analysis and exploitation of next generation of time series (damats)
of Chicago) offers students an introduction to analyzing financial data using methods that are simpler than those he describes in Analysis of Financial Time Series.
Coverage of several mainstream modeling approaches in time series is combined with recent developments in time series analysis in this text for a graduate course on Bayesian time series modeling and analysis.
In the last decade, fuzzy time series has been widely used for forecasting dynamic and non-linear data.