Questions tagged [decomposition]
111 questions
25
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How to decompose a time series with multiple seasonal components?
I have a time series that contains double seasonal components and I would like to decompose the series into the following time series components (trend, seasonal component 1, seasonal component 2 and irregular component). As far as I know, the STL…
ace
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Utility of the Frisch-Waugh theorem
I am supposed to teach the Frish Waugh theorem in econometrics, which I have not studied.
I have understood the maths behind it and I hope the idea too "the coefficient you get for a particular coefficient from a multiple linear model is equal to…
Anthony Martin
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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 out whether there is a trend, seasonality etc.…
MonkeyDLuffy
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statsmodels seasonal_decompose(): What is the right "period of the series" in the context of a list column (constant vs. varying number of items)
Assume having a list column so that your time series is nested, see Convert pandas df with data in a “list column” into a time series in long format. Use three columns: [list of data] + [timestamp] + [duration] for details. The question here is not…
questionto42standswithUkraine
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How to choose the best time window using structural times series with loess
My question is about the Cleveland et al. 1990 paper STL: A Seasonal-Trend Decomposition Procedure Based on Loess. The full citation is:
Cleveland, RB, Cleveland, WS, McRae, JE, and Terpenning, I. 1990. STL: A seasonal-trend decomposition…
aaronmams
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5
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1 answer
Conditional expectation and variable decomposition
Suppose that $X$ and $Y$ have an uknown joint distribution $f_{XY}$.
How can I formally demostrate that it always exists a unique decomposition of the form :
$$ Y = E[Y|X] +\epsilon $$
without assuming any explicity form of $f_{XY}$?
omega
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4
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Decomposing a time series with some zero values
There are many techniques to decompose a time series into trend, seasonal, and remainder components. I was wondering if these techniques can be applied without worry to time series which have some zero values. I think that the answer may be…
John M
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Even after seasonality adjustment, seasonality still remains. Why?
I'm trying the classic AirPassengers dataset in R and tried removing the seasonal component using deSeas <- forecast::seasadj(decompose(d,"multiplicative")), but it doesn't seem to go away.
Original data:
Seasonality viewed with…
Nav
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4
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1 answer
Decomposition of single variable into mean and dispersion around mean
Consider a survey of firms of size $n$. This survey includes, among other variables, the average wage of workers in firm $i$ ($x_i$) and the number of workers in the firm ($L_i$). Both are random variables.
I want to study the properties of the…
luchonacho
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Decomposition of SARIMA models
I use R for time series analysis. I would like to evaluate decomposition algorithms. decompose and stl from "stats" package lead to good results but often, the residuals are not meaningless.
Example:
dec <-…
lkegel
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1 answer
How to account for shifting seasonality arising due to differences between gregorian and Islamic calendars?
I am trying to predict time series through decomposition, my time series is as follows,
As islamic calendars lag the gregorian calendar by 10 days after each year, so my seasonality is also changing, when I try to decompose time series through…
abubakar ilyas
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3
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1 answer
Why does NMF of a symmetric matrix yield orthogonal matrices which are not transpose identical?
Consider the non-negative factorization of a positive, real symmetric matrix A. Non-negative factorization of this matrix yields A = WH where W != H^T.
Yes, there are special cases of A = WW^T factorization, but I understand that this is an imposed…
zdebruine
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3
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Decomposition of Mahalanobis distance: Where's my mistake?
Kim (2000) gives a formula for the decomposition of the (squared) Mahalanobis distance for $d$ variables for a random vector $\mathbf{x}$ with mean vector $\mathbf{\mu}$ and covariance matrix…
COOLSerdash
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How to choose between additive and multiplicative decomposition in time series
I have a time series which is the number of weekly flu cases from 2010 to early 2018 in one county. I want to remove seasonality from my data so I can have a clearer data to infer the relationship with environmental factor PM2.5. I know if the…
Ellie Bayat
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3
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1 answer
How to decide whether to model a time series additively or multiplicatively?
I've been reading a lot of theoretical content on additive and multiplicative decomposition, but when it comes to deciding what type of decomposition to use on my own data I find it kinda hard to do visually. For example, these are some of my data…
Marcos Silva
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