knitr::opts_chunk$set( message = FALSE, warning = FALSE, fig.width = 8, fig.height = 4.5, fig.align = 'center', out.width='95%', dpi = 100, collapse = TRUE, comment = "#>" )
timetk: A toolkit for time series analysis in R
This tutorial focuses on 3 new functions for visualizing time series diagnostics:
library(tidyverse) library(timetk) # Setup for the plotly charts (# FALSE returns ggplots) interactive <- TRUE
m4_hourly %>% group_by(id) %>% plot_acf_diagnostics( date, value, # ACF & PACF .lags = "7 days", # 7-Days of hourly lags .interactive = interactive )
walmart_sales_weekly %>% select(id, Date, Weekly_Sales, Temperature, Fuel_Price) %>% group_by(id) %>% plot_acf_diagnostics( Date, Weekly_Sales, # ACF & PACF .ccf_vars = c(Temperature, Fuel_Price), # CCFs .lags = "3 months", # 3 months of weekly lags .interactive = interactive )
taylor_30_min %>% plot_seasonal_diagnostics(date, value, .interactive = interactive)
m4_hourly %>% group_by(id) %>% plot_seasonal_diagnostics(date, value, .interactive = interactive)
m4_hourly %>% group_by(id) %>% plot_stl_diagnostics( date, value, .frequency = "auto", .trend = "auto", .feature_set = c("observed", "season", "trend", "remainder"), .interactive = interactive)
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