Trend Estimation Task
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A Trend Estimation Task is a estimation task for time series data.
- Context:
- It can be solved by a Trend Estimation System (that implements a trend estimation algorithm).
- It can be used to make and justify statements about tendencies in the data, by relating the measurements to the times at which they occurred.
- It can range from being a Linear Trend Estimation Task to being a Non-Linear Trend Estimation Task.
- Example(s):
- See: Homogeneity (Statistics), Time Series, Linear Function, Randomness.
References
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Linear_trend_estimation Retrieved:2017-10-29.
- Trend estimation is a statistical technique to aid interpretation of data. When a series of measurements of a process are treated as a time series, trend estimation can be used to make and justify statements about tendencies in the data, by relating the measurements to the times at which they occurred. This model can then be used to describe the behaviour of the observed data, without explaining it. Linear trend estimation expresses data as a linear function of time.
In particular, it may be useful to determine if measurements exhibit an increasing or decreasing trend which is statistically distinguished from random behaviour. Some examples are determining the trend of the daily average temperatures at a given location from winter to summer, and determining the trend in a global temperature series over the last 100 years. In the latter case, issues of homogeneity are important (for example, about whether the series is equally reliable throughout its length).
- Trend estimation is a statistical technique to aid interpretation of data. When a series of measurements of a process are treated as a time series, trend estimation can be used to make and justify statements about tendencies in the data, by relating the measurements to the times at which they occurred. This model can then be used to describe the behaviour of the observed data, without explaining it. Linear trend estimation expresses data as a linear function of time.