forecast: Forecast missing values based on a model (set of equations).

In mivanic/forecasteR:

Description

forecast returns the dataframe after the the missing values have been filled using the provided model.

Usage

forecast(data, model, periods, periodColumn, transformation = NULL,
  lowerBounds, upperBounds, solver)

Arguments

data	A dataframe with some blanks in endogenous variables, and a period column
model	A list of equations specifying the relationships among endogenous variables. The names of equations specify endogenous variables that they solve.
periods	For which periods should the simulation be run?
periodColumn	The name of the column with the period values
transformation	A function specifying how the data need to be transformed post each simulation (e.g., define lagged variables)
lowerBounds	An optional list of lower bounds for endogenous variables
upperBounds	An optional list of upper bounds for endogenous variables
solver	A function that can solve a system of equations (accepts model, endogenous, exogenous and return list with "result" as a list of the same structure as endogenous)

Value

A data frame

mivanic/forecasteR documentation built on July 6, 2019, 5:16 a.m.