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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Adjusting decision thresholds for dataset with seasonality component

I am working with data on an infection which exhibits seasonality over the year - the disease tends to be more prevalent during the rainy seasons compared with dry seasons. I'm looking at a binary ...
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Time series deseasoning

The forecasting methods I am interested in include: croston, naive, seasonal naive, ma, adida, exponential smoothing, TSB intermittent demand method). In case the time series contains a seasonal ...
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Time series daily data with weekly seasonality and with some 0 values

I have daily time series data with weekly seasonality and with many 0 values for a number of days throughout the study period. The seasonality increases with time so multiplicative decomposition ...
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How to compare SARIMA to LSTM?

I have a univariate time series which I want to fit a traditional SARIMA model and a LSTM neural network. After that, I want to compare both results to check which one is the best for my case. I am ...
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Time Series Analysis with GAM for daily sales data

I try to analyse the daily product demand of a warehouse which has five product categories. The data is on a daily basis for 7 years. So I want to analyse the seasonal and cyclical patterns (day of ...
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Understanding how seasonal terms are calculated in unobserved components model (statsmodels)- python

Context I am running an unobservedcomponents model from statsmodel api in python The data is daily in nature , and these are the parameters I have set for my model: I have a day of week pattern in ...
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check for seasonality

I am quite new to forecasting and I am currently checking for seasonality. I have already checked for stationarity with the Dickey-Fuller test and didn't find one. I have used seasonal decomposition ...
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Math behind time series multiplicative model for non-constant seasonality

I time series, I know that additive model works better for constant seasonality data while multiplicative model works better for non-constant seasonality. Visually it also makes sense However, I'm ...
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Seasonal ARIMA vs ARIMA with Fourier terms for monthly series

I have monthly data and my goal is to forecast values with an inclusion of exogenous variables. I've built SARIMA and Dynamic Harmonic Regression models, where the second one performs little bit ...
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Estimating SARIMA model with high-frequency data

I want to implement a (double) seasonal ARIMA model and I am looking for a good estimation procedure for high-frequency data. My data contains second-by-second observations and is aggregated to 15 ...
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1answer
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Looking for repeated patterns in time series data

I have spent the best part of the last few days searching forums and reading papers trying to solve the following question. I have thousands of time series arrays each of varying lengths containing a ...
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How to statistically check seasonality in hour/min/seconds data?

I have time-series data that I am trying to examine. It is a dataset of over 100,000 observations that span 12 days and include observations down to the second. I have created plots to look at trend ...
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SARIMA: how transformed data is used during modelling and forecasting

This is something I've been searching around the internet for a while and couldn't really find the answer for. Suppose we have a non-stationary time series ts. I ...
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How to adjust constant/drift to ARIMA forecasting model and how to scale down the cycle up/down size?

I ran ARIMA model on a dataset to forecast the next 180 days sales after training period. My data is daily sales data and is provided here sales data. It has 1267 periods. For the period 729~808, ...
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statsmodels SARIMAX simulate generate negative values?

I read the example code here on how to simulate a time series: Sampling with python statsmodels ARIMA package I used myseries data and it simulated a series. However, the values are negative? I ...
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Interpretation of centered seasonal dummy variables [duplicate]

When estimating a VAR model in R with the VAR()-function from the package 'vars' (https://www.rdocumentation.org/packages/vars/versions/1.5-3/topics/VAR) it allows for inclusion of centered seasonal ...
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Interpretation of centered seasonal dummy variables

When estimating a VAR model in R with the VAR()-function from the package 'vars' (https://www.rdocumentation.org/packages/vars/versions/1.5-3/topics/VAR) it allows for inclusion of centered seasonal ...
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How to decide seasonality Period with 1 year Weather Data?

SO I have 1 year wind Data below composed of 365 daily data, I also tried to decompose it. I tried to do Holt-Winters Exponential smoothing. My plan was to forecast the last 2 months from the data. I ...
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Doubt between deseasonalized ARIMA and SARIMA

I'm new in time series analysis and I'm currently working with a time series that has a trend and a marked seasonalization. As a result, I've detrended and deseasonalized the series before plotting ...
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Time series: Combining trended and periodic series

I have a set of strongly trended time series that are cointegrated (and I think heteroskedastic), and a a strongly periodic but not obviously trended variable that seems to explain some of the ...
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Clustering with strong seasonal data

I'm facing with a cluster request where the purchase behavior in a period of time should be different if compared with the historical data. In other terms the purchase data have a strong seasonal ...
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How to write the analytical equation for the SARIMA model?

If the coefficients for the SARIMA(p, 0, q)(P, 0, Q)[12] model are estimated to be: How do I write the analytical equation of the model? Should it be $X_t = -0.6856 \phi Z_t +0.3983 \phi Z_{t-1} + 0....
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How can I generate seasonal count data that has two different expected values?

The motivation for my question is modelling changes in abundance of a species whose population is estimated from survey data. The challenge for me would be to see if ignoring a food indicator masks ...
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How to interpret the output of ur.df() function in R when using type = "trend"?

When I use ur.df() function without specifying the type, it gives me just one value, Dickey Fuller statistic, with null hypothesis, being that phi = 1+b = 1 => b = 0. That is, delta(yi) is ...
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Time Series Forecasting Arima family methods

I'm fairly new to time series analysis and forecasting. I'm using the uci househould power consumption dataset to build a model to forecast energy consumption. The dataset measures the power (kW) ...
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Moving average filter for estimating the seasonal component

I am reading the Introduction to Time Series and Forecasting Peter J. Brockwell • Richard A. Davis (Third Edition). I am having problems for understanding the estimation of seasonal component using ...
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Should I always remove seasonal component from data

As discussed before, removing seasonal component is in general a good practice for pre-processing data in statistical modeling. My particular question comes from the fact that I'm working with three ...
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How to transform a daily average temperatures forecast into an hourly forecast based on the hourly temperature profile observed historically?

I need to transform a daily average temperatures forecast into an hourly forecast based on the hourly temperature profile observed historically. I work in Python. I have found ways of forecasting the ...
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Exogenous variables SARIMAX

I am trying to model some data as a time series analysis, and I have one exogenous variable that I have reason to believe should have a significant effect on the response. but when I include the ...
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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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Components plots is inconsistent with df_pred on monthly seasonality

Background I do seasonality decomposation with timeseries. In my use case, I have trend/weekly(7 days)/monthly(30.5 days as prophet doc suggests) components. For me, I want to get the data of each ...
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SVAR, seasonality adjustment and impulse response functions

My question might be slightly dumb, however I could not find out which choice would be better. I am trying to construct a SVAR model including the french inflation rate, the unemployment rate and the ...
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Orders of AR and MA models

I have a couple of ACFs and PACFs and cant seem to be sure about the order of AR(p) and MA(q).Can anybody kindly give me an insight into how to detect that?
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Poor results with auto.arima in R

I have the below time series with 361 daily observations (180 observations for year 1 and 181 for year 2). I created the series like this: ...
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What is seasonal-irregular (SI) ratios and its use in seasonal adjustment?

I am involved in some seasonal adjustment (SA) work, and the SI ratios is always computed when I run the X12 ARIMA programs. Hence I would like to understand this statistics better, but I can't find a ...
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How do I add back the seasonal trend?

I worked on to predict the future values of my model but as they had a seasonal trend I had to do a lag differencing of lag=7. But now how do I add back that trend to get original values.
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What does it mean to have only lag significance on certain multiples of 7

I have a dataset named covid and after creating an acf graph of it , it looks something like this Why is it that it is only showing lag significance on lags which are multiples of 7 only , dose it ...
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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, ...
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How do I identify if my time series' seasonality is additive or multiplicative?

The "ExponentialSmoothing" function in Python's "statsmodels.tsa.holtwinters" library gives you the option to set trend equal to ...
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What is the correct way to evaluate time series forecasts with seasonality?

I am working on an energy demand forecasting project, where I am using the Facebook Prophet model. I have used 3 years (2017-2020) of training data to forecast energy demand for a week at an hourly ...
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Regression with SARIMA errors

After an SARIMA transformation, is $\epsilon_t$ equal to the difference in observed original $y_t$ from its estimate or the equivalent quantity for transformed $y_t$, $y'_t$? The motivation: I am ...
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SARIMA explicit formula

I'm trying to expand the $\mathrm{ARIMA}(1,1,2)(1,0,1)[7]$ model to get the explicit formula. Writing the model with polynomial operators should be $$ \phi_1(B)\Phi_1(B^7)(1-B) x_t = \theta_2(B) \...
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Do you need to seasonally adjust covariates prior to ARIMAX modelling?

I found lots of answers in regards to how handle seasonality in dependent variable (time series) though can’t find a definitive answer if we need to seasonally adjust the covariates as well? My main ...
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Residual is identical to Observed in Seasonal Decomposition

I am trying to understand my dataset using the seasonal decompose function from statsmodels. The trend and residuals of my dataset are awkward. I am used to trend being either an upward or a downward ...
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Why strong seasonality in time series of total shipped volumes not observed in customer groups?

In a time series dataset, demand from various customers are given on a daily basis. When the data is aggregated at month level for all the customers together it is easy to see the effect of quarterly ...
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Should I plan my AB testing accordingly to a minimum number of days or to the number of datapoints?

Here's the thing, I was planning to test a new strategy on my website. A typical AB test for a new homepage. One strategy is the current, the control; the other is the variant, the new strategy. I ...
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Recognizing the Seasonal Effects from a Time Plot

From the first plot, I have determined that there is a seasonal pattern of period $L = 12$. However, in my ACF plot (a), it appears that the period is $L = 6$. Am I misinterpreting? The data had a ...
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How to identify a non-periodic time-series?

I am working on a problem where I have to first classify whether a time-series is periodic or not and then, if it is periodic identify its period(s) (the time-series could have multiple periodicities, ...

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