# Questions tagged [decomposition]

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### Can I use the residuals of a time series decomposition to estimate the effect of a covariate?

Context I work for a company that has an e-commerce website. Regularly we make specific campaigns in order to sell more. For example: We can make a campaign for fathers day, black Friday, crazy August,...
462 views

### How to obtain seasonally-adjusted time series data using STL in Python

On the section "STL decomposition" in the 2nd edition of Forecasting: Principles and Practice, it says that the seasadj() function can be used to compute ...
30 views

### Empirical Mode Decomposition(EMD) + CNN for time series forecasting

I'm currently working on a time series project, and I intend to employ the EMD+CNN technique for forecasting the output. Upon applying EMD to the training data, I obtained a total of 14 Intrinsic Mode ...
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### How can I back transform the residuals of a decomposed time series , where I used log(x+c) transformation on the original data?

I did a time series decomposition on a series of Twitter activity data into trend, seasonal and residual component. I checked the distribution of the residuals when fitting a linear model to the time ...
27 views

### Seasonal component inconsistency in X-11 method using R

I am learning about time series decomposition using the X-11 method in R. I am following the book “Forecasting: Principles and Practice (3rd ed)” by Rob J Hyndman and George Athanasopoulos, which uses ...
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### When to Split Data for Time Series Forecasting using Ensemble Empirical Mode Decomposition?

I want to forecast a time series data by using Ensemble Empirical Mode Decomposition (EEMD) and LSTM. However, I'm unsure about when to split the data into training and test sets. Should the data be ...
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### Using statsmodels.tsa.seasonal.seasonal_decompose, my trend line does not cover the entire time period of the data. any words of advice?

I am trying to do a time series decomposition using this1 article as a guide--it uses statsmodels.tsa.seasonal.seasonal_decompose. However, the trend line I get does not extend to the beginning or end ...
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1 vote
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### Seasonal component of STL decomposition looks like the original data

I am doing STL decomposition on Kaggle dataset. Below is just example for one region. I have summed up the values for type (conventional, organic). So data is grouped on date and region. My question ...
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### decompose function show a seasonal graph but there is no correlation in the correlation plot past lag 12 for a monthly dataset. What does it mean?

I generated a TS out of a monthly data. TQ_volume_ts <- ts(csv_file[4:39,"Volume"], start=c(2019,01), frequency = 12) When i apply the decompose function I get the following result: Now ...
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### R: how to interpret the gray bars in the plotted output of the decompose function for time series?

In order to do some time series analysis, I used the decompose() function, to retrieve the adjacent plot. However, I was asking myself about the meaning of the gray bars at the right side. If the show ...
• 103
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### Can you shift a time series and multiplicatively decompose it afterwards to not have negative/zero values

THis question refers to the last unanswered comment in this question: Decomposing a time series with some zero values I see, thank you for the explanation. Let's suppose that the time series follows ...
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### How can I determine best fit for a time series decomposition? [duplicate]

I’m new to time series decomposition and have been doing Seasonal and Trend decomposition using Loess (STL) in R. My data is reported monthly and it appears that seasonality is annual. From what I’m ...
1 vote
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### Wold Decomposition -- summation to infinity

In Wold's decomposition we have $Y_t = \sum_{j=0}^\infty b_j \varepsilon_{t-j} + \eta_t$, where the variables have definition as in the Wikipedia page. I'm confused about why the summation goes to ...
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### Decomposition of a time series based on another time series

I have a general question about decomposition of time series. I have a time series for electricity consumption of one building in hourly resolution for 1 year. This building also has an air ...
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### Why Time series decomposition is performed

I am new to time series forecasting. In most of the forecasting blogs that I have read so far, the time series is decomposed first. As per my current understanding it is suppose to help us in figuring ...
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1 vote
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### What is the most suitable classical decomposition model for the time-series graph? [closed]

To decompose time series data using the classical decomposition method, we have additive as well as multiplicative model. What is the most suitable decomposition model to be used to decompose the time ...