fabletools | General fable features useful for extension packages

by tidyverts R Version: v0.3.1 License: No License

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | fabletools Summary

fabletools is a R library. fabletools has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

The R package fabletools provides tools for building modelling packages, with a focus on time series forecasting. This package allows package developers to extend fable with additional models, without needing to depend on the models supported by fable.

Support

Quality

Security

License

Reuse

Support

fabletools has a low active ecosystem.

It has 72 star(s) with 24 fork(s). There are 12 watchers for this library.

It had no major release in the last 12 months.

There are 42 open issues and 255 have been closed. On average issues are closed in 124 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of fabletools is v0.3.1

Quality

fabletools has 0 bugs and 0 code smells.

Security

fabletools has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

fabletools code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

fabletools does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

fabletools releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of fabletools

Get all kandi verified functions for this library.

fabletools Key Features

No Key Features are available at this moment for fabletools.

fabletools Examples and Code Snippets

No Code Snippets are available at this moment for fabletools.

Community Discussions

Trending Discussions on fabletools

Time series forecasting using Fable in R; determining most optimum combination of models for mixed model

Facet a fabletools autoplot of a fable forecast by model

string as function argument in R inside map

R fable::model() "turn on" progress bar

Why are forecast values slightly lower with `fable::TSLM()` than `stats::lm()`?

'augment()' function in fabletools

Time series forecasting in R; plotting "events" and generating new forecasting plots with specified date range after initial forecast

Does the forecast function within fable provide one-step forecasts?

How can I add exogenous variables to my ARIMA model estimation while using fable package with model() extension

Can't convert a tsibble to a fable

QUESTION

Time series forecasting using Fable in R; determining most optimum combination of models for mixed model

Asked 2021-Dec-07 at 11:04

I am doing some time series forecasting analysis with the fable and fabletools package and I am interested in comparing the accuracy of individual models and also a mixed model (consisting of the individual models I am using).

Here is some example code with a mock dataframe:-

...

ANSWER

Answered 2021-Dec-07 at 11:04

A couple of things to consider:

While it's definitely desirable to quickly evaluate the performance of many combination models, it's pretty impractical. The best option would be to evaluate your models individually, and then create a more simple combination using, e.g. the 2 or 3 best ones
As an example, consider that you can actually have weighted combinations - e.g. 0.75 * ets + 0.25 * arima. The possibilities are now literally endless, so you start to see the limitations of the brute-force method (N.B. I don't think fable actually supports these kind of combinations yet though).

That, said, here's one approach you could use to generate all the possible combinations. Note that this might take a prohibitively long time to run - but should give you what you're after.

Source https://stackoverflow.com/questions/70183054

QUESTION

Facet a fabletools autoplot of a fable forecast by model

Asked 2021-Jul-08 at 18:47

Is there any way to use autoplot with a fable, but facet it by the model? The code below produces a nice little graph, but overlays the forecasts on top of each other.

...

ANSWER

Answered 2021-Jul-08 at 18:47

Maybe this is what you are looking for. As autoplot returns a ggplot object you could simply add facet_wrap(~.model, ncol = 1)

Source https://stackoverflow.com/questions/68306825

QUESTION

string as function argument in R inside map

Asked 2021-Mar-11 at 20:38

Question: i have the following R code (below): It didn't work with "x" = "ARIMA" and "ETS" from "my.list". That's the problem: "fabletools::model(arima_auto = fable::ARIMA(Trips))" = it works, but this: "fabletools::model(arima_auto = fable::x(Trips))" didn't work. Does anyone know the solution to my problem. Is it even possible in R?

...

ANSWER

Answered 2021-Mar-11 at 20:38

When you're calling x(Trips), your x is the character vector "ARIMA". R has no idea what [character vector](Trips) means. It would be like trying to call "Alice"(y) and expecting R to treat "Alice" as a function, even though it clearly is not one.

What you want is a way for R to swap the string "ARIMA" for its corresponding function. This is what match.fun is for. Try this instead:

Source https://stackoverflow.com/questions/66589167

QUESTION

R fable::model() "turn on" progress bar

Asked 2021-Jan-17 at 10:32

How do I "turn on" the progress bar for slower model()s? It seems to be an option according to development in fable and fabletools... but I can't turn it on.

Can someone please tell me what I am missing?

...

ANSWER

Answered 2021-Jan-17 at 10:32

Progress bars can be enabled by wrapping your code with with_progress() from the progressr package. Further customisation can also be found from the progressr package documentation: https://cran.r-project.org/web/packages/progressr/index.html

Source https://stackoverflow.com/questions/65741603

QUESTION

Why are forecast values slightly lower with `fable::TSLM()` than `stats::lm()`?

Asked 2020-Dec-10 at 14:31

I am doing some work which involves modelling values over time, and in the interests of clarity I would like to use the fable package to do this. I want to create a linear model over time with a log transformation - however, I have found that the values generated by fable::TSLM() are in some cases significantly different from those generated by stats::lm(), which has been previously used in the model. It's possible that this issue is caused by my incorrect use of fable functions, however it may also be a bug in the package. The following reprex illustrates my issue:

...

ANSWER

Answered 2020-Dec-10 at 14:31

As stated on link there is a little correction with transformed data in the package fable to produce means instead of medians.

I think it comes from this, as you use a log transformation that modifies the residual law.

Note that if you use point_forecast = list(Fable_Model = median) both models give the same results.

So I guess fable is right

Source https://stackoverflow.com/questions/65235438

QUESTION

'augment()' function in fabletools

Asked 2020-Nov-03 at 06:30

I'm trying to extract the forecast residuals using fabletools package. I know that I can extract the fitted model residuals using the augment() function but I don't know how that works for the forecasted values and I get the same results as the fitted model residuals. Here is an example:

...

ANSWER

Answered 2020-Nov-03 at 06:30

I think you probably want forecast errors --- the difference between what is observed and what was predicted. See https://otexts.com/fpp3/accuracy.html for a discussion. To quote that chapter:

Note that forecast errors are different from residuals in two ways. First, residuals are calculated on the training set while forecast errors are calculated on the test set. Second, residuals are based on one-step forecasts while forecast errors can involve multi-step forecasts.

Here is some code to compute forecast errors on your example.

Source https://stackoverflow.com/questions/64656813

QUESTION

Time series forecasting in R; plotting "events" and generating new forecasting plots with specified date range after initial forecast

Asked 2020-Oct-16 at 13:20

I have created a function which allows me to carry out time series forecasting using the fable package. The idea of the function was to analyse observed vs predicted values after a particular date/event. Here is a mock data frame which generates a column of dates:-

...

ANSWER

Answered 2020-Oct-16 at 13:20

I suppose you could rewrite it this way. I made a couple of adjustments to help you out.

Source https://stackoverflow.com/questions/64388953

QUESTION

Does the forecast function within fable provide one-step forecasts?

Asked 2020-Oct-13 at 06:21

As described here, making one-step forecasts in the test set is a way of avoiding the inevitable increase in variance as a forecast horizon increases. Mentioned in that section are methods to perform one-step forecasts on the test set using an already-trained model, for the forecast package. Is there a similar way of performing a one-step forecast for test data using the newer fable package? Perhaps the new_data parameter described here, for example handles this, but I am not sure, as the forecasts for both h = 24 and new_data = x_test are the same below:

...

ANSWER

Answered 2020-Oct-13 at 06:21

Answer and code

The model argument available for many models in the {forecast} package is equivalent to the refit() method in the {fable} package. When used with future data, it can be used to produce multiple one-step forecasts from a model.

Source https://stackoverflow.com/questions/64320139

QUESTION

How can I add exogenous variables to my ARIMA model estimation while using fable package with model() extension

Asked 2020-Oct-09 at 07:13

I am trying to estimate ARIMA models for 100 different series. So I employed fabletools::model() method and fable::ARIMA() function to do that job. But I couldn't able to use my exogenous variables in model estimation.

My series has 3 different columns, first ID tag identifying the first outlet, then Date.Time tag, and finally the Sales. In addition to these variables I also have dummy variables representing hour of day and week of day.

Following the code given bellow I transformed the dataframe which contains my endegounus and exegenous variables to tstibble.

...

ANSWER

Answered 2020-Oct-09 at 07:13

Here is an example using hourly pedestrian count data.

Source https://stackoverflow.com/questions/64245977

QUESTION

Can't convert a tsibble to a fable

Asked 2020-Sep-28 at 11:57

I do not have a workaround for this at the moment, so desperately looking to solve this issue, no matter how cumbersome as long as my code is working again...

I want to coerce a tsibble to a fable object with:

...

ANSWER

Answered 2020-Sep-28 at 11:57

It's not the most intuitive error message, but I have experienced this before with this function. You actually have to pass Debt to both arguments. I believe the error message references .mean because of an error thrown by an internal function.

Source https://stackoverflow.com/questions/64066980

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install fabletools

You could install the stable version on CRAN:.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: