Out of sample forecast of state space model

Computes out of sample forecasts of a given state space model. Unlike ssm_lm it can manage dummies.

Usage

ssm_lm_oos(
  x,
  trend = FALSE,
  var_intercept = 0,
  var_slope = 0,
  var_variables = 0,
  fixed_var_intercept = TRUE,
  fixed_var_trend = TRUE,
  fixed_var_variables = TRUE,
  date = 28,
  ...
)

Arguments

x: a lm or dynlm model
trend: boolean indicating if the model should have a trend.
var_intercept, var_slope: variance of the intercept (used if ìntercept = TRUE) and the slope (used if trend = TRUE).
var_variables: variance of the other variables: can be either a single value (same variance for all the variables) or a vector specifying each variance.
fixed_var_intercept, fixed_var_trend, fixed_var_variables: logical indicating if the variance are fixed or estimated.
date: choose when we want to start the revision process after the start date. By default set to 28 periods.
...: other arguments used in rjd3sts::estimate().

Value

Returns all coefficients of all variables and the residual