## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>",
                      fig.width = 7, fig.height = 4.2)

## ----setup, message = FALSE---------------------------------------------------
library(shewhartr)
library(ggplot2)
library(dplyr)

## -----------------------------------------------------------------------------
# A 0.5-sigma sustained shift after observation 40
set.seed(2026)
n      <- 80
shift  <- c(rnorm(40, mean = 0, sd = 1),
            rnorm(40, mean = 0.5, sd = 1))
df     <- tibble::tibble(t = seq_len(n), y = shift)

imr  <- shewhart_i_mr(df,  value = y, index = t)
ewma <- shewhart_ewma(df,  value = y, index = t)
cusum <- shewhart_cusum(df, value = y, index = t)

# Position of the first alarm under each chart
first_alarm <- function(fit) {
  hits <- which(fit$augmented$.flag_any)
  if (length(hits) == 0L) NA_integer_ else min(hits)
}
tibble::tibble(
  chart  = c("I-MR", "EWMA", "CUSUM"),
  alarm  = c(first_alarm(imr), first_alarm(ewma), first_alarm(cusum))
)

## -----------------------------------------------------------------------------
fit <- shewhart_ewma(df, value = y, index = t,
                     lambda = 0.2, L = 2.7)
fit
autoplot(fit)

## -----------------------------------------------------------------------------
shewhart_ewma(df, value = y, index = t, steady_state = TRUE) |>
  autoplot()

## -----------------------------------------------------------------------------
fit <- shewhart_cusum(df, value = y, index = t, k = 0.5, h = 4)
fit
autoplot(fit)

## -----------------------------------------------------------------------------
set.seed(1)
baseline <- tibble::tibble(t = 1:60, y = rnorm(60, mean = 100, sd = 2))
mu_hat   <- mean(baseline$y)
sd_hat   <- sd(baseline$y)

new_data <- tibble::tibble(
  t = 61:100,
  y = rnorm(40, mean = 100.8, sd = 2)   # 0.4 sigma shift
)

shewhart_ewma(new_data, value = y, index = t,
              target = mu_hat, sigma = sd_hat,
              lambda = 0.2, L = 2.7) |>
  autoplot()