## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup, message=FALSE----------------------------------------------------- library(lubridate) library(iperform) library(ggplot2) ## ----------------------------------------------------------------------------- data(voix_mobile) ## ----------------------------------------------------------------------------- head(voix_mobile) ## ----------------------------------------------------------------------------- summary(voix_mobile) ## ----------------------------------------------------------------------------- shapiro.test(voix_mobile$Revenu) ## ----------------------------------------------------------------------------- dday(data = voix_mobile, date = "2023-08-11", d = 0, x = "Revenu", unite = 1, decimal = 0) ## ----------------------------------------------------------------------------- dday(data = voix_mobile, date = "2023-12-11", d = 0, x = "Revenu", unite = 1, decimal = 0) ## ----------------------------------------------------------------------------- mtd(data = voix_mobile, date = "2023-08-11", m = 0, x = "Revenu", unite = 1, decimal = 0) ## ----------------------------------------------------------------------------- ytd(data = voix_mobile, date = "2023-08-11", a = 0, x = "Revenu", unite = 1000, decimal = 0) ## ----------------------------------------------------------------------------- wtd(data = voix_mobile, date = "2023-08-11", w = 0, x = "Revenu", unite = 1, decimal = 0) ## ----------------------------------------------------------------------------- full_m(data = voix_mobile, date = "2023-08-11", x = "Revenu", unite = 1000, decimal = 0, cumul = FALSE) ## ----------------------------------------------------------------------------- full_m(data = voix_mobile, date = "2023-08-25", x = "Revenu", unite = 1000) ## ----------------------------------------------------------------------------- forecast_m(data = voix_mobile, date = "2023-08-11", x = "Revenu", unite = 1000, decimal = 0, cumul = FALSE, mod = "NULL") ## ----------------------------------------------------------------------------- vec_date = c("2023-08-20", "2023-08-25", "2023-08-28", "2023-08-30", "2023-08-31") for (d in vec_date) { F = forecast_m(data = voix_mobile, date = d, x = "Revenu", unite = 1000) print(F) } ## ----------------------------------------------------------------------------- taux_v(data = voix_mobile, date = "2023-08-11", x = "Revenu", p = -1) ## ----------------------------------------------------------------------------- taux_v(data = voix_mobile, date = "2023-08-11", x = "Revenu") ## ----------------------------------------------------------------------------- taux_v(data = voix_mobile, date = "2023-08-11", x = "Revenu", variation = "mtd") ## ----overview, eval = FALSE--------------------------------------------------- # overview(data = voix_mobile, # date = "2023-08-11", # x = "Revenu", # unite = 1, # decimal = 2, # cumul = FALSE, # freq = "full") # ## ----echo=FALSE--------------------------------------------------------------- resultat <- overview(data = voix_mobile, date = "2023-08-11", x = "Revenu", unite = 1, decimal = 2, cumul = FALSE, freq = "full") resultat ## ----------------------------------------------------------------------------- df_mb = mean_m(data = voix_mobile, x = "Revenu", unite = 1, decimal = 0) head(df_mb, 10)