PsiForecastLinear(X, known_ys, known_xs[, simulate])
PsiForecastLinear() predicts a future value or values for a time series dataset (containing known or historical data) using linear regression. Passing False as the last argument results in a static forecast. If True is passed for this argument, a random error will be included in the forecasted points
X: The target date. A data point for which you want the predicted value. A data point may be date/time or numeric.
known_ys: An Excel range containing the independent variables in the given dataset.
known_xs: An Excel range containing the time variables in the given dataset.
simulate: (Optional) Pass True or False for the third argument. Passing False (the default) will result in a static forecast that will only update if a cell passed in the known_ys argument is changed. If True is passed for this argument, a random error will be included in the forecasted points.
Note: This function was introduced to coincide with the Excel 2016 Forecast function, Forecast.ETS. This function computes a forecast using exponential smoothing, similar to the PsiForecast function, but uses different argument lists and also differs in other specific details. Analytic Solver (starting with V2018) includes support for this function, so you can use it in your models, with one caveat: If you use this forecast function in an optimization model where the arguments depend on the decision variables, or in a simulation model where the arguments depend on uncertain variables, you may see slightly different calculated forecast values depending on whether the Psi Interpreter or Excel Interpreter is selected in the Task Pane Platform tab. When the Psi Interpreter is used, a slightly different (but arguably better) methodology is used to compute these forecast functions. When the Excel Interpreter is selected, Microsoft Excel is used to calculate the worksheet and thus Excel's methodology will be used.