predict.sim_dlim: Simulated DLIM Predictions

In dlim: Distributed Lag Interaction Model

Simulated DLIM Predictions

Description

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 class '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")

See Also

predict.dlim

Type vignette('dlimOverview') for a detailed description.

dlim documentation built on May 29, 2024, 8:32 a.m.