dynamr: A Permutation-Based Changepoint Technique for Monitoring...

In dnkent/dynamr: A Permutation-Based Changepoint Technique for Monitoring Effect Sizes

Description

dynamr is used to detect where effect values change temporally when estimating generalized linear models with panel data.

Usage

dynamr(dat, time_var, formula, N = 2000, window_size,
  family = c("gaussian", "binomial", "poisson"))

Arguments

dat	Data frame with panel data of interest
time_var	Name of variable denoting time period for any observation, must be a character
formula	Formula for glm object
N	Number of coefficient samples extracted for calculating stable statistical behavior, defaults to 2000
window_size	Number of time periods per model
family	A description of the error distribution to be used for the fitted glm. Currently, there are three options: "gaussian" - multivariate linear regression; "binomial" - multivariate logistic regression; "poisson" – multivariate Poisson regression

Examples

library(ISLR)
library(dynamr)

data("Weekly")

stock_dynam <- dynamr(
 dat = Weekly,
 time_var = "Year",
 formula = Today ~ Lag1 + Lag2,
 window_size = 1,
 family = "gaussian",
 N = 5000
)

stock_dynam

dnkent/dynamr documentation built on June 29, 2021, 7:22 p.m.