Fable -- a FORTRAN 77 to C++ convertor.
Questions tagged [fable]
43 questions
0
votes
1 answer
How to apply Fable/Forecast (in R) to this database?
I am trying to forecast a multiple time series with the Fable function in R. It seems the most eficient way to do it, but I am very new using R so I'm currently dealing with a lot of problems. I just wanted to ask someone for advices and Ideas. I…

AmphaWolf
- 19
- 3
0
votes
1 answer
Irregular time series in fable package
In the tsibble package and fable package, I think I read somewhere that we can handle irregular time series.
I could not find anything with examples on how to do it. Some questions I have are:
Do I have to convert irregular timeseries to a regular…

ok1more
- 779
- 6
- 15
0
votes
0 answers
Interpreting arimax forecast in R fable
I have a lagged ind. variable x which I believe can predict y.
First I fitted a tslm-model and saw that the residuals might be modelled as an arima-process. -> So I modelled the residuals as ARIMAX (1,1,0).
My trouble is understanding why the…

d_fornis
- 29
- 3
0
votes
0 answers
fable box_cox accuracy error and forecast not converting back to original series
I'm following on a previous answer related with fable R and the use of
box_cox function to transform the response variable. When I tried to get the accuracy of model an error occurred. Also when I used the forecast function the series is still…

daandra
- 1
- 1
0
votes
1 answer
Mutate a column in a tsibble dataframe, applying a Box-Cox transformation
I am a big fan of Hyndman's packages, but stumbled with Box-Cox transformation.
I have a dataframe
class(chicago_sales)
[1] "tbl_ts" "tbl_df" "tbl" "data.frame"
I am trying to mutate an extra column, where the Mean_price variable…

Anakin Skywalker
- 2,400
- 5
- 35
- 63
0
votes
1 answer
Rolling Exponential Smoothing
REWRITING ORIGINAL QUESTION
I want a function that takes a vector and pre-defined exponential smoothing model (in this example, simple exponential smoothing with alpha = 0.5), and does one-step ahead forecasting on the input vector. The below code,…

mpettis
- 3,222
- 4
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- 35
0
votes
1 answer
Specify order of ARIMA using Fable package
I am running an ARIMA model using the fable package. Just curious to find out whether there is a way to specify the order of the model (e.g specifying an order of 2,1,1) when using the ARIMA function in the package as opposed to using the optimal…

sa90210
- 525
- 2
- 12
0
votes
1 answer
Null result for ACF1 from accuracy function
I fit a naive model to a time series and got null for the ACF1 column. I thought it should always have a numerical result since it's just a correlation? Why is this null?
Following is my code:
library('fable')
library('feasts')
library('dplyr')
df…

Mushroom
- 17
- 3
0
votes
1 answer
Getting null results from the accuracy function in fabletools package
I have a time series that looks like this
t value
1 12
2 12
3 0
4 0
5 0
6 0
7 0
I expect acf1 to equal 0.443, but instead the accuracy function produces null. The code is as following:
df = data.frame("t" = 1:7, "value" = c(12, 12, 0, 0, 0, 0,…

Mushroom
- 17
- 3
0
votes
1 answer
Dynamically insert variables into a fable model using rlang
I am trying to dynamically insert variables into a fable model.
Data
library(dplyr)
library(fable)
library(stringr)
df <- tsibbledata::aus_retail %>%
filter(State == "Victoria", Industry == "Food retailing") %>%
mutate(reg_test = rnorm(441,…

StephenK
- 685
- 5
- 16
0
votes
1 answer
selecting lagged predictors with TSLM using AICc
I am trying to determine lagged predictors to include in my time series model. So I fitted a TSLM with up to lag 3 of the independent variable
lag_models <- data_train %>% model(
ts_lag_0 = TSLM(Y ~ X)
, ts_lag_1 = TSLM(Y ~ X + lag_X_01)
,…

Punxsutawney
- 81
- 1
- 4
0
votes
1 answer
Why is the constant `fabletools` different from the mean in `forecast` package (ARIMA model)?
I started rewriting all my code from forecast to fable.
Does anybody know why the constant is different from the mean?
library("fable")
library("lubridate")
library("dplyr")
library("forecast")
# gen data
set.seed(68)
df <- data.frame(time =…
user9452375
-2
votes
1 answer
Why is this fitting model giving 1 model per df line
in a normal model fit on a dataset that looks like this :
> head(total)
# A tsibble: 6 x 15 [1D]
# Key: id [6]
Date Close Interest_Rate Consumer_Inflation `CPI(YOY)` `Wage_Index(QoQ)` `Wage_Index(YoY)` AiG_idx TD_Inflation…

user9085964
- 49
- 7