is_forc_general: In-sample general model forecast

In lmForc: Linear Model Forecasting

In-sample general model forecast

Description

is_forc_general takes a model function, a prediction function, input data for estimating the model, realized values of the dependent variable, and an optional vector of time data associated with the model. The model is estimated once over the entire sample period using the input data and model function. Model parameters are then combined with the input data using the prediction function to generate in-sample forecasts. Returns an in-sample forecast conditional on realized values.

Usage

is_forc_general(model_function, prediction_function, data, realized, time_vec)

Arguments

model_function	Function that estimates a model using the data input.
prediction_function	Function that generates model predictions using model_function and data as inputs.
data	Input data for estimating the model.
realized	Vector of realized values of the dependent variable equal in length to the data in data.
time_vec	Vector of any class that represents time and is equal in length to the length of realized and data.

Value

Forecast object that contains the in-sample forecast.

See Also

For a detailed example see the help vignette: vignette("lmForc", package = "lmForc")

Examples

date <- as.Date(c("2010-03-31", "2010-06-30", "2010-09-30", "2010-12-31",
                  "2011-03-31", "2011-06-30", "2011-09-30", "2011-12-31", 
                  "2012-03-31", "2012-06-30"))
y  <- c(1, 0, 0, 0, 1, 1, 0, 0, 0, 1)
x1 <- c(8.22, 3.86, 4.27, 3.37, 5.88, 3.34, 2.92, 1.80, 3.30, 7.17)
x2 <- c(4.03, 2.46, 2.04, 2.44, 6.09, 2.91, 1.68, 2.91, 3.87, 1.63)
dataLogit <- data.frame(date, y, x1, x2)

is_forc_general(
  model_function = function(data) {glm(y ~ x1 + x2, data = data, family = binomial)},
  prediction_function = function(model_function, data) {
      as.vector(predict(model_function, data, type = "response"))
  }, 
  data = dataLogit,
  realized = dataLogit$y,
  time_vec = dataLogit$date
)

lmForc documentation built on Sept. 11, 2024, 8:14 p.m.