Simulated DLIM Predictions

This function estimates cumulative and non-cumulative lag/modifier coefficients from a model in which the response is regressed on a cross-basis generated by the cross_basis() function.

Usage

# S3 method for sim_dlim
predict(object, newdata = NULL, type = c("DLF", "CE", "response"), ...)

Arguments

object: an object of class "dlim"
newdata: vector of modifiers for inference (class "numeric")
type: Type of prediction. "response" for predicted responses, "DLF" for the estimated distributed lag functions, "CE" for cumulative effects (class "character")
...: additional arguments affecting the predictions produced

Value

This function returns a list of 4 or 7 elements:

est_dlim: est_dlim element from predict.dlim (class "list")
cb: cross-bais from object (class "cross-basis")
fit: fit from object (class "lm", "glm", "gam")
true_betas: true_betas from object (class "matrix")
cb_dlm: cb_dlm from object (class "crosspred")
model_dlm: model_dlm from object (class "lm", "glm", "gam")
est_dlm: cumulative and/or point-wise estimates, standard errors, and confidence intervals for the DLM (class "list")

Usage

Arguments

Value

See also