fit_cp_model: Fit Change Point

In aarmiller/predictBoundCP: Find Change-Point using Prediction Bound

Description

Fit Change Point

Usage

fit_cp_model(count_data, low, high, model = "lm", plot = TRUE, level = 0.95)

Arguments

count_data	A dataset of visit counts, must contain variables 'days_since_dx' and 'n'. Where 'days_since_dx' is the number of days since diagnosis (negative values before diagnosis) and 'n' are the number of visits
low	the low value in the training window (i.e., the point closest to diagnosis to include in the training window)
high	the high value in the training window (i.e., the point furthest from diagnosis to include in the training window)
model	the model to be used. Current options include "lm", "exp", "lm_period", "exp_period"

Examples

fit_cp_model(count_data = visit_counts,
             low = 40,high = 180,
             model = "lm",
             plot = FALSE)

aarmiller/predictBoundCP documentation built on Dec. 31, 2020, 6:38 p.m.