¿Cómo puedo hacer que Highcharter represente un objeto de pronóstico?

Question

Apr 03, 2017, 05:34 PM

¿Cómo puedo hacer que Highcharter represente un objeto de pronóstico?

Este es un seguimiento deesta pregunta.

Estoy tratando de obtener la canalización dada en esa pregunta para aceptar un objeto de pronóstico como entrada:

Nuevamente, usando estos datos:

> dput(t)
structure(c(2, 2, 267822980, 325286564, 66697091, 239352431, 
94380295, 1, 126621669, 158555699, 32951026, 23, 108000151, 132505189, 
29587564, 120381505, 25106680, 117506099, 22868767, 115940080, 
22878163, 119286731, 22881061), .Dim = c(23L, 1L), index = structure(c(1490990400, 
1490994000, 1490997600, 1491001200, 1491004800, 1491008400, 1491012000, 
1491026400, 1491033600, 1491037200, 1491040800, 1491058800, 1491062400, 
1491066000, 1491069600, 1491073200, 1491076800, 1491109200, 1491112800, 
1491120000, 1491123600, 1491156000, 1491159600), tzone = "US/Mountain", tclass = c("POSIXct", 
"POSIXt")), class = c("xts", "zoo"), .indexCLASS = c("POSIXct", 
"POSIXt"), tclass = c("POSIXct", "POSIXt"), .indexTZ = "US/Mountain", tzone = "US/Mountain", .CLASS = "double", .Dimnames = list(
    NULL, "count"))

yo suelo

highchart(type = 'stock') %>% 
    hc_add_series(t) %>% 
    hc_xAxis(type = 'datetime')

Crear

Pero si sigo esta misma receta usando

require("forecast")
t.arima <- auto.arima(t)
x <- forecast(t.arima, level = c(95, 80))

highchart(type = 'stock') %>% 
     hc_add_series(x) %>%
     hc_xAxis(type = 'datetime')

Me sale este error:

Error in as.Date.ts(.) : unable to convert ts time to Date class

¿Cómo puedo mostrar la serie de pronósticos junto con el histórico? He visto esto en la documentación, pero no entiendo por qué estaría recibiendo este error.

SALIDA CONSOLA JS PARA JK:DATOS DEL DF DESPUÉS DE RE-INDEXAR:

dput(df)
structure(list(Index = structure(c(1490968800, 1490972400, 1490976000, 
1490979600, 1490983200, 1490986800, 1490990400, 1491004800, 1491012000, 
1491015600, 1491019200, 1491037200, 1491040800, 1491044400, 1491048000, 
1491051600, 1491055200, 1491087600, 1491091200, 1491098400, 1491102000, 
1491134400, 1491138000, 1491217200, 1491220800, 1491224400, 1491228000, 
1491231600, 1491235200, 1491238800, 1491242400, 1491246000, 1491249600, 
1491253200, 1491256800, 1491260400, 1491264000, 1491267600), class = c("POSIXct", 
"POSIXt")), Data = c(2, 2, 259465771, 315866206, 64582553, 233440220, 
91918347, 1, 126563786, 158555699, 32951026, 23, 108000151, 132505189, 
29587564, 120381505, 25106680, 117506099, 22868767, 115898351, 
22878163, 119285747, 22881061, 157925588, 32447780, 223096830, 
281656273, 45406684, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 
    Fitted = c(102170573.857143, 102170573.857143, 102170573.857143, 
    102170573.857143, 102170573.857143, 102170573.857143, 102170573.857143, 
    102170573.857143, 102170573.857143, 102170573.857143, 102170573.857143, 
    102170573.857143, 102170573.857143, 102170573.857143, 102170573.857143, 
    102170573.857143, 102170573.857143, 102170573.857143, 102170573.857143, 
    102170573.857143, 102170573.857143, 102170573.857143, 102170573.857143, 
    102170573.857143, 102170573.857143, 102170573.857143, 102170573.857143, 
    102170573.857143, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 
    `Point Forecast` = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 102170573.857143, 102170573.857143, 102170573.857143, 
    102170573.857143, 102170573.857143, 102170573.857143, 102170573.857143, 
    102170573.857143, 102170573.857143, 102170573.857143), `Lo 80` = c(NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -16003477.5789723, 
    -16003477.5789723, -16003477.5789723, -16003477.5789723, 
    -16003477.5789723, -16003477.5789723, -16003477.5789723, 
    -16003477.5789723, -16003477.5789723, -16003477.5789723), 
    `Hi 80` = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, 220344625.293258, 220344625.293258, 220344625.293258, 
    220344625.293258, 220344625.293258, 220344625.293258, 220344625.293258, 
    220344625.293258, 220344625.293258, 220344625.293258), `Lo 95` = c(NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -78561041.5917782, 
    -78561041.5917782, -78561041.5917782, -78561041.5917782, 
    -78561041.5917782, -78561041.5917782, -78561041.5917782, 
    -78561041.5917782, -78561041.5917782, -78561041.5917782), 
    `Hi 95` = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, 282902189.306064, 282902189.306064, 282902189.306064, 
    282902189.306064, 282902189.306064, 282902189.306064, 282902189.306064, 
    282902189.306064, 282902189.306064, 282902189.306064)), .Names = c("Index", 
"Data", "Fitted", "Point Forecast", "Lo 80", "Hi 80", "Lo 95", 
"Hi 95"), row.names = c(NA, -38L), class = "data.frame")