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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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How to remove non-constant seasonality in panel data?

I have a panel data with daily crime rates over seven years. In my regression I control for year, month-of-year, and day-of-week fixed effects (as well as county fixed effects). However, the residuals ...
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mstl for multiple-frequency time-series where the frequencies are unknown

I create 2 data, the 1st repeats in 5 terms, the 2nd repeats in 15 terms. Then they are summed up and converted to ts using default setting. ...
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How to remove seasonality from time series?

I want to model time series in Python for air quality prediction. My dataset has two columns: date_time and aqi, and contains hourly measurements of AQI. Data is seasonal but not perfectly seasonal ...
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How to fit a GAM with double seasonality to a daily time series? (mgcv package)

I'm trying to adjust a Generalized Additive Model to a daily time series. My goal is to do a short-term forecast for the gas demand of my city. I have data since 2015, including information about the ...
Emilia A.'s user avatar
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371 views

Time-series prediction of 15 min interval data

I have 5 years 15 min interval of electricity demand time series with a datetime index and a target variable. Don't have any other data to use. I'm curious about your experiences. In general how far ...
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Short-term gas demand forecasting

I'm a 22 year old Statistics student with a big problem to solve. English isn't my first language, so I apologize in advance for any mistakes in my grammar. I'm trying to make a short-term gas ...
Emilia A.'s user avatar
1 vote
1 answer
286 views

Fourier feature for multi seasonality

I am trying to forecast a univariate time series with multiple seasonality Something like this: library(forecast) fit <- auto.arima(y, seasonal=FALSE, xreg=fourier(y, K=8)) Based on visualization ...
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How to forecast a series (daily power consumption) with multiple seasonalities?

I wish to forecast electricity power demand at a mall. Data is collected daily, but, the data has multiple seasonality : data/power consumption is generally similar from monday to thursday but see a ...
Anant's user avatar
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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, ...
abubakar ilyas's user avatar
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2 answers
432 views

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 ...
Thomas Bilach's user avatar
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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 ...
zemni houssem's user avatar
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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 ...
StatisticsJonSnow's user avatar
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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 ...
iditbela's user avatar
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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 ...
RandomR's user avatar
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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 ...
Tom's user avatar
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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 ...
3 votes
2 answers
317 views

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 ...
Robert Sun's user avatar
3 votes
1 answer
177 views

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 ...
Stats IT's user avatar
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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 ...
Crystal Snow's user avatar
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0 answers
126 views

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: ...
Dan Scally's user avatar
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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 ...
Fernando's user avatar
1 vote
2 answers
1k views

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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2 votes
2 answers
5k views

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 ...
lucaskain's user avatar
1 vote
1 answer
473 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) ...
Huy Huynh's user avatar
3 votes
2 answers
2k views

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: ...
Papa_fern's user avatar
1 vote
1 answer
190 views

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, ...
user241668's user avatar
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3 answers
2k views

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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1 vote
1 answer
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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 <...
Artem Moskalev's user avatar
2 votes
1 answer
456 views

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 ...
dakotalk's user avatar
3 votes
0 answers
1k views

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 ...
Michieldo's user avatar
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1 answer
223 views

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 ...
saravanan saminathan's user avatar
2 votes
1 answer
383 views

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 ...
user218838's user avatar
2 votes
1 answer
2k views

What is ARMA error in time series?

I heard a term "ARMA ERROR" in BATS and TBATS. How it helps in time series forecasting.
saravanan saminathan's user avatar
4 votes
2 answers
3k views

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 ...
user10129792's user avatar
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1 answer
101 views

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. ...
M. T.'s user avatar
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6 votes
2 answers
1k views

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?
paf's user avatar
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2 votes
0 answers
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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, ...
Thomas R's user avatar
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0 answers
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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 ...
spv92's user avatar
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0 answers
936 views

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 ...
Felix Thoemmes's user avatar
1 vote
0 answers
80 views

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-...
Alexey Burnakov's user avatar
1 vote
1 answer
2k views

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: ...
Carolus Fridericus's user avatar
2 votes
0 answers
252 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 ...
Technologic's user avatar
4 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 ...
Nick Barnes's user avatar
12 votes
1 answer
11k views

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 ...
Kumar Manglam's user avatar
4 votes
1 answer
237 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. ...
Paula's user avatar
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