LinForecast

Syntax

LinForecast(Year1, Value1, Year2, Value2,... YearN, ValueN) or
LinForecast(XLRange(Filename, Rangename))

Description

Linear forecasting is used to estimate future values based on a time-series of historical data. The new values are predicted using linear regression assuming a linear trend (y = mx +c) where the Y term corresponds to the variable to be forecast and the X term is years. Linear forecasting is most suitable in cases where exponential growth in values is not expected: for example when forecasting how market shares or technology penetration rates might change over time.

Use this function with caution. You may need to first use a spreadsheet or some other package to test the statistical validity of the forecast (i.e. test how well the regression "fits" the historical data). Moreover, bear in mind that future trends may be markedly different from historical ones, particularly if structural or policy shifts in the economy are likely to have an impact on future trends.

Using the above two alternatives syntaxes the time-series data required by the function can either be entered explicitly in WEAP as year/value pairs or it can be specified as a range in an Excel spreadsheet. Use the yearly time-series wizard to input these values or to link to the Excel data. In either case, years do not need to be in any particular order, but duplicate years are not allowed, and must be in the range 1900-2200.

When linking to a range in Excel, you must specify the directory and filename of a valid Excel worksheet or spreadsheet (an XLS or XLW) file, followed by a valid Excel range. A range can be either a valid named range (e.g. "Import") or a range address (e.g. "Sheet1!A1:B5"). The Excel range must contain pairs of years and values in its cells arranged into 2 columns. Use the WEAP Yearly Time-series Wizard to select a worksheet, to choose among the valid named ranges in the worksheet, and to preview the data that will be imported.

NB: The result of this function will be overridden by any value calculated for the Current Accounts. In some cases this may lead to a marked "jump" from the Current Accounts value to the succeeding year's value. This may reflect the fact that the Current Accounts year you have chosen is not a good match of the long-term trends in your scenario, or it may reflect a poor fit between the regression and the historical data.

Tip

Use the Yearly Time-Series Wizard to enter the data for this function.