futurera | open data, time series, forecasting

Equation:

Y^t = at + b

, where Y^t is the value of the time series at time t, and a and b are estimated from the data using least-squares estimation.

An example serie is in the Examples Data as Lineair Trendcurve.

With the method slopes. we get the slopes characteristics of the demand serie.

It seems that a horizontal line is a good fit for the slope characteristics. The slope of a straight line is constant, implying that Y^t is increasing by a constant amount each period; if the slope is plotted against time a horizontal straight line is obtained and this is the required slope characteristic.

Many lines can be drawn. One that the application suggest is shown in the graph.

This is calculated with Trend, then the Line option in the application.
Parameters: start year (2004) and end year (2017).

Equation where Y is the trend line.

Y^t = 52.9t + 1048.5

Potential application: The linear curve type is useful for data that increases or decreases steadily with time. For example, this tool can be used to forecast the populations of communities during the stage of development in which the population growth is approximately linear.

Serie is in the Examples Data as Lineair Trendcurve.

SUMMARY