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 remove variations in a time series X caused by another time series Y?

I have a time series on a monthly basis (a commodity) of which much variation is caused by the weather. I want to adjust this commodity for weather changes. I use Heating degree day as a proxy for ...
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1answer
39 views

Strange results in Holt forecast

I am trying to understand what could be causing these strange values to appear on applying a Holt model to a vector. The data represents actual sales of an item. ...
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1answer
60 views

Testing for a drop in bookings

We're developing real-time alerts for fine-grained (every 5 minutes) time series bookings data, and I'm looking for the best approach to doing this. Idea is that if over the past 10–15 minutes (say) ...
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57 views

time series is obviously periodic, but seasonal decomposition is not working in R

my time series is obviously periodic, but the seasonal decomposition using stl() is not working in R: ...
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1answer
164 views

Visualizing large dataset with multiple subgroups

I have a large data frame in the following form (I apologize for this formatting): ...
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22 views

Using day length and rate of change of day length in linear regression

I have a time series in which samples were collected approximately monthly over ten years. I have wanted to identify whether a number of bacterial species were seasonally variable and whether they ...
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20 views

Non-fixed seasonality in time series

I believe some time series data I am looking at shows seasonality according to general elections (UK, so this can be 4 or 5 years). How do I remove this effect in R?
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23 views

Repeated measures analysis… or not?

Not sure if dealing with repeated measures analysis...? Measuring X at 3 seasons (summer, winter, spring/fall) during a year – might be high summer/low winter, high winter/low summer, consistently ...
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67 views

Periodogram vs. spectral density diagram of a time series

Could someone explain to me the difference between a periodogram and spectral density diagram? The first diagram is produced with this block of code: ...
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26 views

What is usefulness of time series decomposition if building a multivariate model?

I am at the early stages of building a panel regression model of sales data. I know my final model dataset will consist of log sales, control variables and log media variables. I am planning to use ...
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34 views

On the Fly Time Series modeling

I'm dealing with a system which monitors and records a time series (half hourly) which I plan to use to build a double seasonal time model (if possible using something that already exists, such as ...
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24 views

X12 Seasonal adjustment: levels, differences or growth rates?

So far I used X12 casually for informative analysis etc. But now that I require precision - I stumbled upon a problem: What transformation of data is intended for most accurate results? I can ...
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39 views

Trend and seasonality tests for a univariate time series

I am working with a batch of about 1000 univariate time series in R . For every time series, I have to perform following tasks , before deciding upon a model be it ARIMA, TAR or Holt Winter's Model ...
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19 views

Seasonal Data with Yearly “Step” Trend

Trying to plan for upcoming inventory needs for a clothing company. There is a strong seasonal component to the data. At the beginning of the year, sales are up; at the end, sales are down. Each ...
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63 views

Forecasting time series with trend and seasonality

I have a univariate time series, which has a trend and month seasonality. Traditionally I have been using auto.arima() method in R to model such series. So when I ...
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3answers
70 views

How to prove that one variable's change is influenced by another variable; that is to say, are they related?

I major in bioinformatics. We all know that temperature changes during a year. I find that a disease incidence is really high when temperature is relatively high, while it becomes really low when the ...
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1answer
117 views

Multivariate biological time series : VAR and seasonality

I have a multivariate time series dataset including interacting biological and environmental variables (plus possibly some exogenous variables). Beside seasonality, there is no clear long-term trend ...
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1answer
87 views

How to interpret R stl() output

I want to have a logical interpretation of the results of my stl analysis. ...
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0answers
105 views

R - ARIMA model with long seasonal periods - Error: “length of x and xreg does not match”

i want to use an ARIMA model in R for predicting an electrical load on a minutely basis. By examining the ACF I figured out which model could suit. The ACF has shown that the value one day ahead has a ...
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1answer
165 views

ARIMA with difficult seasonality in R

I have non-stationary time series. It has evident trend in means and seasonality. These raw data are measured every second. On the plot of original series I see trend and seasonality about 80,81 ...
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1answer
140 views

Using anomalies to calculate trends of seasonal data

I commonly see people doing trend analysis of (monthly) timeseries data which show a strong inter-annual cycle following this scheme: compute climatological means ("mean January", "mean February", ...
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3answers
137 views

Deterministic components in covariates/exogenous variables in time series models

Actually, I have read a pair of books about time series analysis, but I am still not sure about how to treat deterministic components, like trend and seasonality, in the exogenous variables in a time ...
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1answer
108 views

Creating alert system based on standard deviation and mean: How to deal with small sample size, trends and seasonality?

I'm trying to build a daily alert system to let me know when something unusual has happened in my analytics data that might require further investigation. Right now I'm taking 7 weeks worth of data, ...
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1answer
209 views

Problem defining ARIMA order

This is a long post so I hope you can bear with me, and please correct me where I'm wrong. My goal is to produce a daily forecast based on 3 or 4 weeks of historical data. The data is 15 minute ...
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2answers
120 views

Treatment of triple seasonal data

I have a data set of electricity spot prices, which contains three kinds of seasonality: one within 24 hours, one within a week and one within a year. I want to use an R package (...
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2answers
119 views

How to predict demand from historical “continuous” event data (date, lat, lon)?

I am attempting to predict demand for our service, both quantity but maybe more important, location (hotspots). I am by no means an experienced statistician, so I need some help :) I have all the ...
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2answers
706 views

Forecasting hourly time series with daily, weekly & annual periodicity

Major edit: I would like to say big thanks to Dave & Nick so far for their responses. The good news is that I got the loop to work (principle borrowed from Prof. Hydnman's post on batch ...
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1answer
67 views

Frequency on Tbats function in R

I have 3 complete years + 4 weeks of weekly time series data, of which one of the years is a leap year. To calculate its frequency should I do (365x2+366)/(3*7)? Thanks!
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2answers
76 views

Seasonality criterion?

I'm working on a model of saving account amounts. It shows a seasonality: On the 1st day of every month the amount always decreases. This is reasonable as people probably need draw money to pay ...
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293 views

Ratio-to-moving average method

I'm working on a model that the data has seasonality. To decompose the seasonal part, I'm looking at wiki page where there's an example using “ratio-to-moving average method”. However, I'm a bit ...
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1answer
236 views

Why does auto.arima() give negative output?

This is the dataset on which I am working currently, which is production data. Data: ...
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2answers
177 views

Why is normalizing seasonal adjustment factors done additively?

One of the methods for dealing with seasonal influence is to establish a multiplicative factor for each season within a "year". For example, this happens with exponential smoothing models of type ...
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2answers
192 views

Seasonal dummies significance issues

I have a question concerning the significance of the seasonal dummies in my ARIMA-model (I do not use seasonal differencing or seasonal AR/MA as I have quite regular seasonality and I get better ...
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1answer
135 views

Residuals in double seasonal exponential smoothing

I have a time series with muliple seasonal cycles, which are 24 and 168 hours for my case. I would like to use Double Seasonal Exponential Smoothing method to forecast, which was published by James W. ...
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1answer
235 views

Including seasonality in regression

I am regressing monthly data that I know has significant seasonality. I have about 50 monthly observations. I was thinking of using 12 variables and for each row of my data turn on one variable ...
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1answer
71 views

What does seasonality of 1 mean?

What does having a seasonality of 1 mean? Suppose I have hourly data and I define the seasonality to be 1, does that mean the data will be dealt with as if there is no seasonality?
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269 views

How to model month to month effects in daily time series data?

I have two time series of daily data. One is sign-ups and the other terminations of subscriptions. I'd like to predict the ...
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267 views

ARIMA forecasting with external regressors

I am trying to build ARMAX models using auto.arima. I have a time series to forecast (weekly and monthly seasonality, I've put the ts() frequency=7), another two time series as external regressors, ...
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190 views

Best practices for dealing with shifting, inconsistent seasonality

This question is related to a previous post I've looked at (Calculation of seasonality indexes for complex seasonality), but deals with more granular data (daily instead of weekly), and transforming ...
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1answer
563 views

ARIMA and external regressors in SAS and R

So I remember reading somewhere that when we have external regressors, auto.arima cannot make correct predictions for the order of difference for either ...
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90 views

Harmonic or dummy seasonal model

Within the BFAST package in R, one of the parameters that it gives is the choice of seasonal model parameter (harmonic, dummy, or none). I understand what none does; However, I didn't really ...
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1answer
550 views

Time series deseasonalization

How do you know when deseasonalization is not necessary? That is, from what I understand, if you want to just look at the trend and irregular components of a time series, then you just need to remove ...
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3answers
965 views

Identify seasonality in time series data [duplicate]

I want to detect presence of seasonality in time series data. I know one can achieve that by plotting the autocorrelation function but I need an automatic process if the series is seasonal or not, ...
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1answer
252 views

using stl (seasonal decomposition with loess) for weekly data

I am trying to decompose a weekly time series using the R function 'stl'. One of the important argument of this function is the number of data per cycle. Naturally in this case one would choose 52. ...
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174 views

Seasonality Period in ARIMA function in R - How to Interpret

I've used the ARIMA function in R to fit my data to the best possible model. My data consists of daily information and there ...
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1answer
228 views

What to do about Seasonality Patterns in ACF, Time Series Data

I'm dealing with a time series data and I'm trying to construct a time series model for this particular dataset. I'm new to R and tried using the the auto.arima ...
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1answer
693 views

ARIMA forecast with seasonality and trend, strange result

as I am stepping into forecasting with ARIMA models, I am trying to understand how I can improve a forecast based on ARIMA fit with seasonality and drift. My data is the following time series ( over ...
2
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1answer
153 views

ARIMA modeling: can seasonal data be seasonally stationary?

I am new to ARIMA modeling and currently encountering a weird situation with time series of count data. The time plot shows clear seasonal patterns.ACF also hints on presence of seasonality. However, ...
2
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0answers
79 views

Seasonal component for a series that is only one and a half years

I have a times series for temperature and I am trying to decompose it into a seasonal + trend + stochastic process to look at what model would fit for the stochastic process. However, I only have ...
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2answers
463 views

What is the best way to strip weekly and seasonal noise from a time series data set?

What is the best way to strip weekly and seasonal noise from a time series data set? Any recommendations on different approaches and there relative benefits?