time-series data

information collected over a number of time periods with respect to a given variable such as income. Compare CROSS-SECTIONAL DATA.

Collins Dictionary of Economics, 4th ed. © C. Pass, B. Lowes, L. Davies 2005

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- Simplified operations that allow users to focus on working with time-series data and eliminate the headaches of managing a database.

TIMESCALE INTRODUCES TIMESCALE CLOUD

Time-series data obtained from sensors does not include anything other than every-changing numerical data.

Fujitsu Develops Automatic Labeling Technology to Accelerate AI Use of Time-Series Data

Much of today's big data is time-series data, so having specific functions for time is crucial.

Don't Get Washed Out by the Overflowing Data Lake: Five Key Considerations

Time-series data is complex, explains Greg Olsen, senior vice president, products.

Using Pattern Recognition to Improve Industrial Operations

[11] Philippe esling and Carlos agon, "Time-Series Data Mining," ACM Computing Surveys, Vol.

Clustering Algorithm for Time Series with Similar Shapes

Having published a book of aggregated time-series data on the demography, economy, infrastructure, and society of the four US and six Mexican states on the border between the countries, Reich here adds a legal dimension to this quantitative overview.

The Law of the United States-Mexico Border: A Casebook

The historian product handles time-series data, as well as alarm and event data.

Brewer scales smart manufacturing platforms for next decade

It is commonly used to model time-series data on the attempt to explain and predict macroeconomic variables such as GDP, investment, consumption, spending, exports, imports, employment and unemployment.

MACROECONOMETRICS: STATISTICAL ALCHEMY AT THE FINAL STAGE

Manolopoulos, "Feature-based classification of time-series data," in Information Processing and Technology, M.

A Cycle Deep Belief Network Model for Multivariate Time Series Classification

Generally, there are two types of gene expression data used to predict the structure of GRNs, which are steady-state data and time-series data. The steady-state data measures the steady-state levels in different samples, while time-series data measures the expression levels at several successive time points.

Inference of Gene Regulatory Networks Using Bayesian Nonparametric Regression and Topology Information

Time-series data consists of hundreds or even thousands of measurements taken at recurring time intervals.