Tagged Questions

2
votes
0answers
17 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 ...
1
vote
0answers
20 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 ...
0
votes
1answer
45 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 ...
0
votes
3answers
96 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, ...
0
votes
0answers
37 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 ...
1
vote
1answer
55 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 ...
2
votes
1answer
93 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 ...
1
vote
2answers
129 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?
2
votes
2answers
201 views

Treating non-stationarity of time series in seasonal adjusted data with R

I'm currently trying to use a variable x (and others) to explain a dependent variable y in a distributed lag model (with the long term goal of predicting variable y). The plot of variable x shows an ...
3
votes
2answers
209 views

Two seasonal periods in ARIMA using R

I'm currently using R to predict a time series with these instructions: ...
2
votes
2answers
215 views

Handling forecast mean with complex seasonality

I'm using a time-series model to do weekly forecasts on the number of incoming calls to a company. This variable has a weekly 'in-month' pattern and a monthly 'in year' pattern, and i have data from ...
3
votes
1answer
124 views

Criteria to set STL s.window width

Using R to perform STL decomposition, s.window con­trols how rapidly the sea­sonal com­po­nent can change. Small val­ues allow ...
0
votes
1answer
123 views

What's the best model to analyze inflation seasonal adjustment with R?

Please, put in R the following structure: ...
4
votes
1answer
104 views

Contraindication for STL decompostion

Trying to "understand" a time series' patterns it is intuitively tempting to use STL decomposition as the concept of distinguishing between trend, season and the rest makes sense. But my experience ...
0
votes
1answer
299 views

Calculate trend slope after STL decomposition

I have a time-series of daily measurements of some quantity for 1995-2011. There's about one measurement every three days. The data show a strong seasonality (annual cycle). What I ultimately want ...
2
votes
1answer
187 views

I can't tell whether my data are seasonal or just affected by calendar effects

I used to think my time-serie was seasonal, but then I realized it simply needed some calendar-effect adjustment. I tried that and I'm now in doubt there might still be some seasonality left. I tried ...
5
votes
1answer
219 views

Seasonally adjusted month-to-month growth with underlying weekly seasonality

As a side hobby, I have been exploring forecasting time series (in particular, using R). For my data, I have the number of visits per day, for every day going back almost 4 years. In this data there ...
-8
votes
1answer
155 views

Business forecasting [closed]

Data can have trends, cycles, seasonal pattern repeats and irregular components. How do these components impact on the ordinary multiple regression with dummy variables?
1
vote
1answer
435 views

Characteristics of gold prices in an ARIMA model analysis

I'm forecasting gold prices using an ARIMA model. An ARIMA model requires a stationary, non-seasonal, linear series. However, after reading a few books, it seems that gold price data is ...
1
vote
0answers
96 views

Seasonal Unit Root

I would like to ask a question about the Dickey, Hasza and Fuller seasonal unit root test. Is there any material on the web or maybe the paper of the three (DHF) that describes the test calcualtions ...
4
votes
5answers
4k views

What method can be used to detect seasonality in data?

I want to detect seasonality in data that I receive. There are some methods that I have found like the seasonal subseries plot and the autocorrelation plot but the thing is I don't understand how to ...
2
votes
1answer
189 views

Outlier detection in short time series with two seasonalities

I have short daily time series (less than 4 years) representing sales and exhibiting two seasonalities (weekly and yearly) and I am seeking to identify outliers (not only data reporting errors but ...
4
votes
2answers
4k views

Auto.arima with daily data: how to capture seasonality/periodicity?

I am fitting an ARIMA model on a daily time series. Data are collected daily from 02-01-2010 to 30-07-2011 and are about newspaper sales. Since a weekly pattern in sales can be found (the daily ...
6
votes
2answers
162 views

Estimating event probability from historical time series with clear seasonality

I would like to predict the average number of days in a year for which two conditions are true: daily average temperature is below zero celsius the day was preceded by at least four days with daily ...
14
votes
2answers
661 views

Choosing seasonal decomposition method

Seasonal adjustment is a crucial step preprocessing the data for further research. Researcher however has a number of options for trend-cycle-seasonal decomposition. The most common (judging by the ...
8
votes
2answers
896 views

Calculation of seasonality indexes for complex seasonality

I want to forecast retail items (by week) using exponential smoothing. I'm stuck right now in how to calculate, store, and apply the sesonality indexes. The problem is that all examples I've found ...