Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/",
dpi = 300,
fig.width = 5,
fig.height = 3
)
## ----setup--------------------------------------------------------------------
library(cusumcharter)
library(ggplot2)
## -----------------------------------------------------------------------------
test_vec <- c(1,1,2,3,5,7,11,7,5,7,8,9,5)
test_vec
## ----baseplot, fig.width=5, fig.height=3--------------------------------------
test_vec <- c(1,1,2,3,5,7,11,7,5,7,8,9,5)
variances <- cusum_single(test_vec)
p <- qplot(y = variances)
p <- p + geom_line()
p + geom_hline(yintercept = 0)
p
## ----singledf-----------------------------------------------------------------
variance_df <- cusum_single_df(test_vec)
variance_df
## ----baseplot2,fig.width=5, fig.height=3--------------------------------------
p <- qplot(y = variance_df$x)
p <- p + geom_line()
p <- p + geom_hline(yintercept = variance_df$target)
p
## ----cusumcontrol-------------------------------------------------------------
cs_data <- cusum_control(test_vec)
cs_data
## ----cusumcontrolplot,fig.width=5, fig.height=3-------------------------------
cusum_control_plot(cs_data,xvar = obs)
## ----controlplotshow,fig.width=5, fig.height=3--------------------------------
cusum_control_plot(cs_data,xvar = obs, show_below = TRUE)
## ----facetcontrolplots,fig.width=5, fig.height=3------------------------------
library(dplyr)
library(ggplot2)
library(cusumcharter)
testdata <- tibble::tibble(
N = c(-15L,2L,-11L,3L,1L,1L,-11L,1L,1L,
2L,1L,1L,1L,10L,7L,9L,11L,9L),
metric = c("metric1","metric1","metric1","metric1","metric1",
"metric1","metric1","metric1","metric1","metric2",
"metric2","metric2","metric2","metric2","metric2",
"metric2","metric2","metric2"))
datecol <- as.Date(c("2021-01-01","2021-01-02", "2021-01-03", "2021-01-04" ,
"2021-01-05", "2021-01-06","2021-01-07", "2021-01-08",
"2021-01-09"))
testres <- testdata %>%
dplyr::group_by(metric) %>%
dplyr::mutate(cusum_control(N)) %>%
dplyr::ungroup() %>%
dplyr::group_by(metric) %>%
dplyr::mutate(report_date = datecol) %>%
ungroup()
p5 <- cusum_control_plot(testres,
xvar = report_date,
show_below = TRUE,
facet_var = metric,
title_text = "Highlights above and below control limits")
p5
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