Linked Questions

0 votes
0 answers

General methods to deal with time series data [duplicate]

Sorry I'm new to machine learning and statistics. For time series predictions, do you use RNN or something? For example, the past 2 years' sales of a product. TBH Im pretty much unfamiliar with how ...
user900476's user avatar
1 vote
0 answers

Learning materials about Time Series Forecasting? [duplicate]

I am a beginner in Time Series Forecasting meaning I have created some simple forecasting models and used them and I am also familiar with Stats and Probability but not that good just some basic ...
Anurag Bhatt's user avatar
146 votes
19 answers

Books for self-studying time series analysis?

I started by Time Series Analysis by Hamilton, but I am lost hopelessly. This book is really too theoretical for me to learn by myself. Does anybody have a recommendation for a textbook on time ...
10 votes
2 answers

What would be a good model to fit to cumulative reputation on Stack Exchange?

I'm trying to model the distribution of my cumulated reputation on one Stack Exchange site over time (that is, each data point is the sum of my reputation whenever that reputation changes, mostly ...
Ben's user avatar
  • 215
4 votes
2 answers

find the difference between the expected sales and the actual sales

A little bit of background: I have daily demand data for our product from 1 January 2017 to 31 December 2022. Sometime after Covid-19 struck say 1 March 2020, the sale of our product went up ...
Jash Shah's user avatar
  • 267
3 votes
1 answer

How do quantile time series forecasts work?

My office leadership is interested adopting “quantile time series forecasting”, the idea is query the model to predict the 5th, 25th, 50th, 75th and 95th percentiles of an RV given features such as ...
jbuddy_13's user avatar
  • 3,244
3 votes
1 answer

Does the absolute value of MAPE or sMAPE have meanings?

Let say I have a forecasting system compared with a naive forecast that just use the today's value as forecast. If the naive forecast have a MAPE of 200%, and my system have a MPAE of 100%, could I ...
Mahali Sindy's user avatar
4 votes
1 answer

ARIMA model on yearly data using R

Im new to time series forecasting, and I was trying to model the folowing time series data using ARIMA model in R, so that I can predict for the future 10 time periods. data: cereal_dataset When I ...
Dominic Joseph's user avatar
2 votes
0 answers

Accuracy metric for comparing Time Series models?

I'm writing a blog post on forecasting time series with autoregression. In it, I compare the performance of SLR, ARIMA, and SARIMAX on forecasting the number of Home Sales in Seattle (see below). All ...
infinitely_improbable's user avatar
0 votes
1 answer

Time series analysis hourly data Python SARIMAX or better another ML-Algorithm

I am working on my bachelor thesis with time series data. The idea is to predict the expected battery life based on voltage data from sensors. During my research I came across SARIMAX. For me this ML ...
Maximiliami's user avatar
2 votes
2 answers

Incorporating ARIMA errors in a linear regression model

I am working with economic data and trying to create a linear regression model for forecasting purposes. The dependent variable data is in terms of percentage change and I've differenced the ...
Amy K's user avatar
  • 151
4 votes
1 answer

Is there a name for a fallacy, when a word is understood colloquially instead of technically? [closed]

I sometimes encounter a view that only perfect forecasting is really forecasting. For example, if I claim that I have a model which forecasts election results, people will think I'm making the ...
user4945913's user avatar
2 votes
1 answer

Do I have look-ahead bias?

I have a prediction task at hand, and I'm deciding on how to sample my data and train a model with no look-ahead bias. Given a time series $Z$, my task is to build a simple predictor of size $m$ (...
arash's user avatar
  • 189
1 vote
1 answer

Adjusted R2 for LSTM

Background: I am working on a problem, where I am making predictions for a time-series data. I am considering two approaches: Use LSTM, predict n samples using recursive strategy (suggested e.g. in ...
Michał Panek's user avatar
2 votes
1 answer

ARIMA: Understanding how time series analysis is focused on mathematical properties as opposed to best forecasts

Rob Hyndman states: "The paper describing the competition [M] (Makridakis et al, 1982) had a profound effect on forecasting research. It caused researchers to: ... treat forecasting as a ...
ColorStatistics's user avatar

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