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Questions tagged [fable-r]

R package for tidy time series forecasting (fable: Forecasting Models for Tidy Time Series)

fable: Forecasting Models for Tidy Time Series

Provides a collection of commonly used univariate and multivariate time series forecasting models including automatically selected exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA) models.

These models work within the 'fable' framework provided by the 'fabletools' package, which provides the tools to evaluate, visualise, and combine models in a workflow consistent with the tidyverse.

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R fable aggregate with mean

require(dplyr) require(fable) require(tsibble) Build a simple tsibble object d <- tibble( t = c(1:15, 1:15), f = rep (letters[1:2] , each = 15), x = c(rpois(15, 10), rpois(15, 1))) d <- as_tsibble(d, index = t, key = f) Provide the…
Andrea
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Incorporating external regressor in a hierarchical/ grouped time series

Fellow contributors, I have been working with a hierarchical time series, relating to a set of identical products in a number of stores. For this purpose when we aggregate the data set based on 2 attributes like "store" and "product_type" in my…
Anoushiravan R
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How to get multiple-steps ahead forecast with STL model in fable-r?

My purpose is forecast multiple-step without re-estimation. And I will update new observation to next forecast. I did not using fit and apply forecast(h=7) because this function using fitted value to forecast next observation. I used following codes…
BinhNN
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Is there an R function that can plot the PACF() of an ARIMA model in the fable, feasts or fpp3 packages?

I am working with a tsibble created from a csv file and I have begun following along Rob Hyndman's fpp3 textbook creating ARIMA models with the fable package. My goal is to plot the PACF of the given ARIMA model. This is inspired by following along…
Daniel Lupercio
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ARIMA Modeling running time issue

My data set is a weekly data that contains two variables Production and Shipment. Production is the independent variable and Shipment is the dependent variable. First I'm trying to forecast Production values and use that as a regressor to forecast…
Arvind Menon
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How to specify annual seasonality for an ARIMA model of fable

I am having trouble specifying seasonality in an ARIMA model of the fable package. I have a dataset with daily data and want to take into account annual seasonality. I make use of the Daily Electricity Price and Demand Data which can be found on…
David W.
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Automatic ETS from fable package in R does not provide the model with the lowest Information Criteria (AIC, BIC and AICc)

Using the classic shampoo dataset from fpp2 I tried to fit an automatic ets model. This led me to an ETS(A,A,N) framework with aic = 441.0668, bic = 448.9844 and AICc = 443.0668. Nevertheless when using an ETS(A,M,N) model the information criteria…
Andre Gutierrez
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Error while Plotting the Cross correlation values using astsa package in R

The dataset I have is a weekly data with one dependent and Independent variable with One grouping Variable(which is the Key variable). I'm able to get the cross-correlation values between Dep. & Ind. Variables based on the grouping variable using…
Arvind Menon
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Forecasting in R using one grouping variable

I'm trying to forecast the year-month data with one grouping variable which is "Actual Delivery location". I'm using ARIMA from Fable package for the forecasting but i'm getting the following error when I run the model Error message : 3 errors (1…
Arvind Menon
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not able to install 'fable' package (ERROR: compilation failed for package ‘fable’)

I am trying to install fable running the command install.packages("fable"), as it says in https://cran.r-project.org/web/packages/fable/readme/README.html however i am getting the following: It says clearly that it is because i don't have llapack,…
Mangostino
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how to extract fitted values in a forecast model after multiple model simulations

This is my original df and fitted model library(tsibble) library(tibble) library(ISOweek) library(fable) library(forecast) library(fpp3) library(dplyr) library(tidyverse) Original.df <- structure(list(YearWeek = c("201901", "201902", "201903",…
Arvind Menon
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Looking for an example of intervention variables in Forecasting Principles and Practice

I'm working through the book Forecasting Principles and Practice. Specifically, I'm working through the section on Useful Predictors which is here: https://otexts.com/fpp3/useful-predictors.html. The text mentions intervention variables, but I'm not…
Russ Conte
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Fable TSLM different models yield identical predictions

I'm trying to fit and forecast TSLM models with different time-t predictors added alongside the trend... for reasons I don't understand, several of the models yield identical predictions even though the the input test data appears different, and the…
ADF
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Refit an arima model with new training data in fable package

I have a function which takes a fitted model and then refits that model to new training data (this is for step-ahead cross validation). For lm models it works like this: #create data training_data <- data.frame(date = seq.Date( from =…
jay
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no non-missing arguments to max; returning -inf error with mutate

I have data as shown in the Shiny app code below. This data is a filtered part of a dataframe which has many Keys. The way I have filled in the gaps in the tsibble, there are N in the RSEXCL column in between Y's. I would like to make it so that if…
LauraDR
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