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Questions tagged [seasonality]

Seasonality refers to the recurring fluctuation around the mean of a time-series for a given period of time, usually a calendar year.

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How to Add Trend to a First Differenced Model for More Accurate Predictions

I've developed a reasonable time-series model on first differenced data. The end goal is to be able to forecast an actual value, not a differenced value. From reading other posts I learned that the ...
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Converting nonstationary process

I am looking at the hourly load demand profile for an entire year. See image below. However, from my understanding of stationarity, this process is non stationary as it has seasonality as well as a ...
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Time series seasonality: mismatch between season length and data collection frequency

I'm working with vegetation data (NDVI collected from MODIS) that is collected at 16-day intervals. I'm doing a time series analysis on a particular site to see how it changes over time. I've already ...
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No autocorrelation in time series

I am trying to predict a time-series data set, using python. I have a timestamp and number of calls in a network for this particular timestamp. I have to predict number of calls in the future. ...
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Find multiple frequency in a time series

In a time series model, my data contain two or more seasonal pattern such as week and annual. But I don't know it's frequency initially, Is there is any method that will figure out all the frequency ...
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Why is the Trend component of this Chistiano-Fitzgerald filter (mFilter's cffilter) so overfitted?

The goal: I am attempting to extract the seasonal and trend component from a time series using a band pass filter, due to issues with loess-based methods, which you can read more about here. The ...
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How to control the long-term and seasonal trends in the time-series using DLNM in monthly data?

Suppose that Yt, denotes the monthly case number of an infection disease of the whole city at calendar time ( month ) t , and follows a Poisson distribution by Yt | μt ~ POI(μt), where μt is the ...
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Advice on correcting for seasonality in data

I am a little new to time series in general, however, I have 5 years of weekly sales data and another variable of interest. I am trying to see if there is a trend in the sales data and the second ...
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What ARIMA to use

I have a data set which generally decreases over 24 period units. It then returns to its relatively highest state at the beginning of the period. So for instance the data may look like this: Period 1 ...
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Forecasting seasonality with Fourier terms in R

I am using the auto.arima from the forecast package in R to determine the optimal K-terms for fourier series. After I do that, ...
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51 views

How to use Partial Autocorrelation (PACF) to determine the exact seasonal period in SARIMA model

I am currently using PACF values to determine the length of seasonal period which are further used in fitting SARIMA model. I use 90-day history to forecast for 30 days. My current method is to ...
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How to globally determine (Seasonal) ARIMA Parameters

I have 15-minutely data (96 values per day) over several years for around 340 entities (i.e. 340 data sets or long ts). Now my task is to forecast a 4-hour window (i.e. 16 observations) for each day ...
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ACF plots before and after removing seasonality

In order to illustrate the effect of cleaning out predictable seasonalities, I plotted some autocorrelation functions before and after removing seasonalities. Before I cleaned the data for predicable ...
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How to deal with seasonality in cointegration analysis?

I have two time series of daily gasoline prices (1500 observations each) which I suspect to be cointegrated. I aim to find an ECM/Asymmetric ECM/Threshold ECM to investigate possible asymmetries. My ...
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Covariance Estimation of time series with mixed frequencies

I have three times series $x_{1,t}$, $x_{2,t}$ and $x_{3,t}$. For the first two time series ($x_{1,t}$ and $x_{2,t}$) I have daily data, but for the last one, I have monthly data (let us assume that ...
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Calculating seasonality and trend of a time series data with clusters

I have this time series data, now I want to calculate the trend seasonality type (multiplicative or additive) for each cluster of APMC(means the area/region) and commodities using price. The dataset ...
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1answer
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Modelling Idea for Big Jumps in Revenue

I'm trying to model some year-on-year data, as seen in the picture, each line represents a different year. From 52 to 0 (x-axis) are the weeks leading up to the last point on the left. I have been ...
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Detecting seasonality from periodogram and seasonplots

I want to determine whether a time series contains seasonality, and if so, what the periodicity is so I can include this as Fourier terms in my model. Because I have to do this for approximately 100 ...
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Usage of findfrequency() in time series prediction

Consider a case where I have a time series data but no information about what the data is about and its frequency. Now I use findfrequency() function of forecast ...
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Searching for a weekly rhythm in weight loss/gain

Asking for a friend, who has read this. Basically my friend weighs daily and has historical data in CSV format. They would like to take that data and overlay it in some form of weekly chart. E.g ...
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Metric to evaluate accuracy of time series decomposition?

I am trying to de-seasonalize a large number of business sales data. They all come from the same industry and follow idiosyncratic seasonality patterns. The number of businesses is quite large, and I ...
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1answer
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Deseasonalize data - strange plot

I want to deseasonalize my daily data, and I chose to verify yearly seasonality as I have prices of wheat that usually increase around the same time of the year. I have used the function ...
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1answer
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Decomposition of seasonal time series interpretation

I have the below stl() (with s.window="periodic") decomposition plot of a time series which I would like to analyse and model. ...
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Econometric models? [closed]

I'm confused about econometrics models. Let's say I used a daily stock market index for 5 years, and I want to see how oil price affect the stock markets return , let's assume ( as a fact ) that oil ...
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Time series analysis - Seasonal variation problem [closed]

I am having trouble with taking out seasonal problem in the data. If you see the picture, the error messg saying "non-numeric argument to binary operator". How should I fix this problem?
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Is the Dickey-Fuller tests is a seasonality test as it tests the existence of the unit root?

Knowing that the "Dickey-Fuller tests" tests if the times series is stationary or not by testing the existence of the unit root, after fitting the time series to AR(1) process. Does "Dickey-Fuller ...
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Intuition about Exponential Smoothing parameters?

If I use Triple Exponential Smoothing with Additive Seasonality and let a statistical program optimize alpha, beta and gamma for me, is there something I can conclude about my data based on the ...
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1answer
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SARIMA model with SARIMA residuals

I currently about to work my way into the time series model a former colleague om mine implemented: it is a SARIMA model (seasonal ARIMA) with SARIMA residuals. First I want to give a brief ...
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R STL and forecast package seems to get confused on this simulated data

I have simulated data according to this DGP: ...
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Best way to visualise timing of seasonal events?

I have a spreadsheet in which I track various seasonal event – first snow, arrival of migratory birds, that kind of thing. You can view it here. What I would love to do is be able to visualise – as I ...
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1answer
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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 ...
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Weekly forecasts when some predictors are monthly

I would like to forecast at the weekly level, but some of the predictors are at the monthly level. The only way I can think to approach this problem is to divide the monthly total by the number of ...
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Meaning of “13-term Henderson filter” [closed]

I wonder what the "13" stands for in the "13-term Henderson filter" seasonal adjustment method. I don't understand the meaning of "13" in this method.
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Time-series: Using decomposed components (seasonality+trend) as covariates in multiple regression?

I need to evaluate the effects of a treatment on a time-series data-set by comparing multiple dependent variables to a prior time period without treatment in effect. I'm using a python library to ...
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Evaluating Mann-Kendall trend test assumptions

Disclaimer: I don't have very much statistics experience.. I do have yearly climate data (yearly max temperature, total yearly precipitation...) for 200 years and want to perform the Mann-Kendall ...
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118 views

Seasonal model with auto.arima

I'm trying to fit a seasonal arima model with the following very simple timeseries which has also a linear trend: time_series = ts(c(6, 18, 30, 80, 65, 40, 67, 47, 57, 82, 67, 82, 66, 78,...
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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 ...
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1answer
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What does an ARIMA model with 6 values mean?

I am trying to get my head around ARIMA modelling. I get the idea of it at least on a superficial level. Looking around you see a lot about ARIMA(p,d,q) where p is the autoregressive term, d is the ...
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Do annual means need to be depersonalized before trends?

I have a time series of annual means of air temperature. I am going to find its long-term trend (~100 years) and have two questions: Knowing that the air temperature is highly seasonal in a monthly ...
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1answer
190 views

Interpreting Regression Coefficients in time series model with seasonal & trend component AND a lagged variable

I'm working on a time series model which predicts daily sales. The model is based on seasonal-trend decomposition by Loess, basically. (I'm using an R package similar to Prophet by facebook.) Since ...
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1answer
70 views

Seasonal ARIMA estimate with non-significant variance

I'm trying to fit a seasonal ARIMA model for a real data time series, 300 samples long, sawtooth looking. I'll write down a resume of my work trying to be clear without many plots. The ACF of the ...
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Should I include both Lag 1 and Lag 4 in this autoregressive model?

Question Background: Thomas Anderson, CFA, is a research analyst at Frank Capital Consultants, a provider of statistical modeling and financial advice to clients globally. Thomas is working on the ...
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Seasonal Adjustment of Daily Data

[![enter image description here][1]][1]I have daily data with only weekday values. So my week is 5 days in my data set. I want to use TBATS function in R. I am ...
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X-13ARIMA-SEATS Errors in R

I'm trying to run a relatively simple seasonal adjustment using the seasonal package in R and I keep getting an error of Error: X-13 has run but produced no data Because of how my data is ...
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59 views

Multiplicative decomposition for DECREASING level of seasonality?

I am performing data exploration on commodity futures volatility. I am using data that supports Samuelson's hypothesis that futures contracts expiring in the nearer term have a higher volatility. ...
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How to run seasonality analysis on a subset data

Data set: multiple product sale volumes by month (product A, B, C, D, E) I want to analyze the data and find out the seasonality component for each product relative to each other (for example ...
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45 views

Sum of seasonality equal to zero and normality of cycle component

In a time series, why do we require the seasonal component sum to zero over a season? Also, is the mean of the cycle component normalised to zero? I know it is too make the components uniquely ...
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2answers
136 views

Time Series Forecast - Complex seasonality

I have a daily time series that I am having issues forecasting accurately.The time series is stationary and it looks I have tried ARIMA(3,1,1),(0,1,1)- 7 Period, auto.arima(D=1), Holt-Winters, nnetar,...
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Stable seasonality F-test does not meet assumptions for one way ANOVA

I am having trouble to understand Stable seasonality F-test. I know it is basically the same test as one way ANOVA, but the assumptions for one way ANOVA can´t be met for it. For ANOVA the data should ...
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How do I add seasonal & trend components to the final prediction when using neural networks?

I've got a question about stationarity: let's say I've made seasonal & trend adjustment for my time series input, scaled it and then passed this data to some NN model (e.g., LSTM or windowed-MLP), ...