fit_cp_profile: Generate Change Point Profile

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

Description

Generate Change Point Profile

Usage

fit_cp_profile(
  count_data,
  low,
  high,
  models = c("lm", "exp", "lm_period", "exp_period", "auto_arima"),
  levels = c(0, 0.9, 0.95),
  window_grid = NA
)

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)
models	the set of models
levels	the set of levels

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