Questions tagged [multiple-seasonalities]

Time series may exhibit multiple seasonalities, e.g., retail sales have intra-weekly and yearly seasonality, and electricity load (and price) has intra-daily, intra-weekly and yearly seasonality.

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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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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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2 answers
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Sinusoidal unit-specific time trends

Suppose I have a panel dataset with monthly observations over 10 years. I have a simple dummy intervention, where some policy is put in place around the Spring in every year and only affects some ...
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Times series forecasting , why predictions are the same over time

This is my first time posting here , I am doing an energy consumption forecast , my data contains the energy every hours I have two seasonality ,every 24 hours and every 7 days (daily and weekly). I ...
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Understanding the period/cycle of time series data

I'm trying to understand the meaning of period/cycle length in time series forecasting. Some functions, such as seasonal_decompose and ...
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Fitting a distribution to historical prices data per month/day of week/hour

I am trying to fit statistical distributions to electricy prices, more precisely EPEX Day-Ahead market prices, per month / day-of-week and hour. Indeed, the prices exhibit very strong seasonnalities ...
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How can I "remove" variability in my data that is due to periodic signals, such as Temperature, RH and Solar radiation?

I have a measured signal that I know is affected by some periodic signals, such as Temperature, RH and Solar radiation. Is there a way that I can "remove" their influence from my measured ...
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SARIMA - Sales predicitons

My question is about seasonality with SARIMA. With data sales, there is (in my opinion) two factors to take into account. Sales have a week seasonality and also a trend throughout the year. My ...
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Measuring Strength of Trend and Seasonalities for Time-Series presenting Multi-Seasonal Patterns

My goal is to cluster time-series which may present daily/weekly/yearly seasonalities. To do so, I plan to use different variables and among them, the following ones: $F_{s_{daily}}$, $F_{s_{weekly}}$ ...
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What is the difference between single seasonal pattern and multiple one?

My problem is most probably trivial. Many books and articles present informations about single and multiple seasonal patterns or single/multiple seasonality. Unfortunately I can't understand the ...
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time series prediction model with minute data

I m trying to apply prediction at my data that is taken from the sensor after 15 min ...
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Resources for learning the time series stuff they don’t (or didn’t) teach you

I at one point, a long time ago, had two years of graduate econometrics focusing on time series, plus more on micro cross-section techniques. I haven’t made much use of the time-series stuff for a ...
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Why the seasonality of daily time series is not predicted correctly in R with arima model?

I have a question related to the estimation of arima models in R. I have estimated a model with daily simulated data where Mondays have a lower value than the rest of the days. I have simulated two ...
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3 votes
1 answer
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Time series when seasonality appear due to both solar and the lunar calendars

I have a time series data as shown in the figure below where the X axis is the serial number of the day of the year form 1 to 365 where 1 is 1-Jan and 365 or 366 is 31-Dec. The Y axis represents the ...
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One year of historical data with yearly and daily seasonality

I have 14 months(01/07/2018 to 30/08/2019) of one minute data, which I have aggregated to 10 mins block. So I have a data of dimension "61056 * 350". From this I am using 12 months of data to train ...
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why is it that mstl decomposition models the higher frequency first?

I'm looking at the code for mstl decomposition and also at this mstl explanation and I see that the higher frequency seasonality (e.g. hour-of-day) is modeled first, the series is de-seasonalized and ...
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Removing multiple seasonalities from time series

I'm using statsmodels.tsa.seasonal.seasonal_decompose to remove seasonality from a time series. I can remove a seasonal component in this way: ...
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Creating a model that projects sales but adjusts for decreased traffic in a retail store

I have data for a retail shop for all of last year (well for many years but this is what I will be using) and all of this year current. The entries are the traffic (# of visitors), the sales, the ...
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What model to fit given ACF and PACF (seasonal data)

I have highly seasonal data, (it's energy consumption) with mostly 24 hour and 168 hour (=1 week) periods and I have applied differencing by 168 hours (...
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Time series forecasting with hour data, prediction for next 24 hours

i'm a newbie in Time Series Analysis. I have a 2 year pandas dataframe about water consumptions in hour granularity (24 records for day, 365 days). Water_consumptions Data ...
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1 answer
223 views

How to fit an ARIMA model with multiple/complex seasonality in R

My dataset contains the following information aggregated into 5-minute intervals over one month: average vehicle speed in km/h time of the observations the day of the week Thus having 288 (12*24) ...
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2 answers
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Forecasting data with multiple seasonality

I'm attempting to forecast the number of taxi rides per hour that occur in NYC. I've turned the data into a time series using 24*7 as the frequency: ...
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1 answer
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TBATS decompostion and how to distinguish "real" sesonality

I am doing exploratory data analisis with TBATS decomposition, to get understand better seasonal patterns behind number of booking. One of my coworkers proposed that there is two weekly seasonality, ...
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3 answers
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Forecasting hourly time series [closed]

I have the following time series: Data is aviable here data The time series represent an hourly eletricity load. It starts at 2018-09-13 19:00:00 and end at 2018-12-23 15:00:00. I want to predict ...
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Maximum number of Fourier terms in forecast package

I am using the forecast package in R to get some Fourier components - namely, function fourier(ts, K, ..). For a time series <...
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Modeling academic seasonality with hierarchical GAMs

I am trying to model the seasonality of daily pageviews to calculus-related Wikipedia articles using a hierarchical GAM, assuming that there is a shared 'academic calendar' seasonality and that each ...
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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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Will VECM handle multiple seasons?

I have two questions: Since VAR (vector autoregression) will not handle seasonality and trend. VECM comes into play which can handle season as well as trend. I had a doubt whether it will handle ...
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2 votes
1 answer
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ARIMA Time series analysis forecasting [closed]

I am having a small project on Time series analysis for that I have hourly sales data for that I need to forecast hourly sales for the next 1 month, i.e around next 720 hours I am exploring ARIMA for ...
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2 votes
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What is ARMA error in time series?

I heard a term "ARMA ERROR" in BATS and TBATS. How it helps in time series forecasting.
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2 answers
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Time Series Forecasting - Hourly Data

I have data from a call center morning 8 am to evening 8 pm with half an hour intervals. I am trying to perform time series forecasting to predict expected number of calls during the same time frame ...
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1 answer
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Which model to use when dual-seasonality is present?

I have an hourly time series that contains 2 forms of seasonality: hourly and weekly. In other words, the hour of the day and the day of the week both have a large impact on the time series values. ...
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Multiseasonal models for multivariate time series

Does there exist model (ideally implemented in R) which take into account multiseasonality for multivariate time series as BATS does in the univariate case?
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What method should I use to forecast discrete data?

I have data which can take discrete values (between 0 and 5). I have 2 values per day during 2 years which contain a lot of 0 and 5. I know that my data are correlated with end of week, end of month, ...
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No suitable ARIMA model found error

I am trying to forecast the sales for next 48 days from the data given by modelling for multiple seasonality and day of week , promotional effects. R could not come up with a suitable model. I need ...
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ARIMA forecast - more than one seasonal trend?

I am using a Kaggle dataset on noise complaints in NYC (https://www.kaggle.com/somesnm/partynyc/version/4) as a teaching example. The time series has exact time and date of the noise complaint but ...
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Stationarity between measurements of categorical variables when testing a hypothesis

Please bear with me on this question, it's a follow on from my other question on a similar topic but in this question I wish to understand how to handle periodicity when testing a hypothesis with ...
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6 votes
1 answer
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LSTM NN produces "shifted" forecast (low quality result)

I am trying to see the power of recurrent neural calculations. I give the NN just one feature, a timeseries datum one step in the past, and predict a current datum. The timeseries is however double-...
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1 vote
1 answer
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Deseasonalizing a time series with multiple seasonalities based on a linear model

I have 3 seasonal components in my data. I wanted to estimate each of them. The result is the following: ...
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2 votes
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217 views

How to decompose seasonality of a time series with a limited time span?

I am working on a time series that contains daily sales data over 2 and a half years. The aim of the project is to estimate the impact of marketing expenditure on the sales, while accounting for ...
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3 votes
2 answers
3k views

Dealing with multi seasonality in time series

I am new in R and time series analysis and need some help. I am currently trying to create a tool to forecast the demand of power for a company. On my data set I have 17550 observations that ...
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9 votes
1 answer
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Is stl a good technique for forecasting, instead of Arima?

I have a long time series(data at hourly level, for 6 years). The data is showing an hourly, a weekly, a monthly as well as a yearly trend. For this data, should I try ...
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4 votes
1 answer
228 views

Removing seasonality from multiple time series

I'm building a model involving a few times series, let's call them A and B. I removed seasonality from A using a function with a linear trend, days of the week and statistically significant months. ...
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forecast daily data for not near future

I am trying to get a forecast for the rest of 2017 based on 5 years of daily historical data. Im having issues with the weekly seasonality I am trying to use the ...
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Why is TBATS smoothing out the forecast when given data with multiple seasonality?

We use the TBATS model for the multiple seasonal data that we have. The data has a weekday season and an hour season, that is, Monday 7 PM is different from Sunday ...
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Efficient forecasting of daily and weekly seasonality in minute data

If I naively apply STL, Holt-Winters or Kalman-Filter approaches to the problem of extracting the seasonality and trend components of a one-minute data stream, I will end up with about 10K cyclic sub-...
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What is a value that can be used to indicate the seasonality of data?

I am looking at different airports and have data on the amount of passengers per month for years 2012-2016. I need to be able to compare the extent to which traffic fluctuates from month to month, ...
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Multiple seasonal time-series : interpret tbats.components() function results in R

I'm using the TBATS model of the forecast package with Google Analytics data, to forecast web trafic containing multiseasonal effects (...
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4 votes
1 answer
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How to estimate weekly and daily seasonality for data with 15min frequency in Python?

I am relatively new to time series. My goal is to predict a few hours of data, measured every 15min based on three months of observations in Python. I assume I have daily and weekly cycles which I ...
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Literature on identifiability of multiple seasonality

A straightforward interpretation of identifiability of seasonal patterns as an ability of a method to extract seasonal pattern or patterns correctly from an artificially created signal does not appear ...
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