pois_vcm_cv: pois_vcm_cv: Cross-Validation for Poisson Time-Varying...

In inqs909/tvcm: Time-Varying Coefficient Models

Description

This function conducts a leave-one-out cross-validation approach to determine the best bandwidth for the data.

Usage

pois_vcm_cv(
  formula,
  data,
  time,
  id = NULL,
  bandwidths = NULL,
  kernel = "epanechnikov"
)

Arguments

formula	A formula class object. Provides information about the names of the response and predictor variables.
data	A data frame containing the variables needed for the function.
time	The name of the variable indicating the time points for each observation.
id	The name of the variable to group observations. Necessary when dealing with repeated measurements such as longitudinal data.
bandwidths	A vector containing the bandwidth values for the cross-validation. Default is tests 50 bandwidths from ranging from double the smallest time point difference to range of time points.
kernel	The name of the kernel function used to estimate the varying-coefficient values. Default is Epanechnikov.

Value

pois_vcm_cv returns a list containing the results from the cross-validation

• recommended_bandwidth: The bandwidth with the smallest negative log-likelihood.

• value: value of negative log-likelihood at recommended bandwidth

• neg_logliks: The tested bandwidths and their corresponding negative log-likelihood value.

Author(s)

Isaac Quintanilla Salinas

Examples

cv_fit <- pois_vcm_cv(formula = Y~x1+x2, data = pois_data, time = time, id = id)

summary(cv_fit)

inqs909/tvcm documentation built on Dec. 20, 2021, 7:03 p.m.