Time series are data observed over time (either in continuous time or at discrete time periods).
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11answers
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Simple algorithm for online outlier detection of a generic time series
I am working with a large amount of time series. These time series are basically network measurements coming every 10 minutes, and some of them are periodic (i.e. the bandwidth), while some other ...
10
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4answers
2k views
Seeking certain type of ARIMA explanation
This may be hard to find, but I'd like to read a well-explained ARIMA example that
uses minimal math
extends the discussion beyond building a model into using that model to forecast specific cases
...
13
votes
2answers
1k views
Proper way of using recurrent neural network for time series analysis
Recurrent neural networks differ from "regular" ones by the fact that they have a "memory" layer. Due to this layer, recurrent NN's are supposed to be useful in time series modelling. However, I'm not ...
17
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5answers
1k views
Efficient online linear regression
I'm analysing some data where I would like to perform ordinary linear regression, however this is not possible as I am dealing with an on-line setting with a continuous stream of input data (which ...
21
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3answers
2k views
Is it possible to do time-series clustering based on curve shape?
I have sales data for a series of outlets, and want to categorise them based on the shape of their curves over time. The data looks roughly like this (but obviously isn't random, and has some missing ...
12
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4answers
2k views
Period detection of a generic time series
This post is the continuation of another post related to a generic method for outlier detection in time series.
Basically, at this point I'm interested in a robust way to discover the ...
5
votes
3answers
476 views
What to make of explanatories in time series?
Having worked mostly with cross sectional data so far and very very recently browsing, scanning stumbling through a bunch of introductory time series literature I wonder what which role explanatory ...
3
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1answer
2k views
How to correlate two time series with gaps and different time bases?
I asked this question over on StackOverflow, and was recommended to ask it here. Rather than duplicate the entire question here, I hope I can start new comment/solution chains here. If I should ...
12
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5answers
3k views
Books for self-studying time series analysis?
I started by Time Series Analysis by Hamilton, but I am lost hopelessly. This book is really too theoretical for me to learn by myself.
Does anybody have a recommendation for a textbook on time ...
15
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9answers
2k views
Time series for count data, with counts < 20
I recently started working for a tuberculosis clinic. We meet periodically to discuss the number of TB cases we're currently treating, the number of tests administered, etc. I'd like to start ...
8
votes
3answers
3k views
How to fit an ARIMAX-model with R?
I have four different time series of hourly measurements:
The heat consumption inside a house
The temperature outside the house
The solar radiation
The wind speed
I want to be able to predict the ...
9
votes
5answers
1k views
How to detect a significant change in time series data due to a “policy” change?
I hope this is the right place to post this, I considered posting it on skeptics, but I figure they'd just say the study was statistically wrong. I'm curious about the flip side of the question which ...
22
votes
5answers
4k views
Time series 'clustering' in R
I have a set of time series data. Each series covers the same period, although the actual dates in each time series may not all 'line up' exactly.
That is to say, if the Time series were to be read ...
9
votes
2answers
922 views
Getting started with neural networks for forecasting
I need some resources to get started on using neural networks for time series forecasting. I am wary of implementing some paper and then finding out that they have greatly over stated the potential of ...
5
votes
3answers
838 views
Outliers spotting in time series analysis, should I pre-process data or not?
My question builds on a previous post on outlier detection in generic time series, and specifically on the answer provided by the always great Rob H.
I work for a small-sized manufacturing company ...
9
votes
4answers
6k views
How many lags to use in the Ljung-Box test of a time series?
After an ARMA model is fit to a time series, it is common to check the residuals via the Ljung-Box portmanteau test (among other tests). The Ljung-Box test returns a p value. It has a parameter, h, ...
7
votes
2answers
1k views
Predicting daily electricity load - fitting time series
I want to predict inter-day electricity load. My data are electricity loads for 11 months, sampled in 30 minute intervals. I also got the weather-specific data from a meteorological station ...
13
votes
2answers
1k views
Testing significance of peaks in spectral density
We sometimes use spectral density plot to analyze periodicity in time series. Normally we analyze the plot by visual inspection and then try to draw a conclusion about the periodicity. But has the ...
8
votes
2answers
585 views
Box-Jenkins model selection
The Box-Jenkins model selection procedure in time series analysis begins by looking at the autocorrelation and partial autocorrelation functions of the series. These plots can suggest the appropriate ...
7
votes
3answers
328 views
What is the term for a time series regression having more than one predictor?
It's pretty tough to search the Web for info on something when you don't know what words are commonly used to describe it. In this case, I'm wondering what it's called when you include another ...
4
votes
2answers
503 views
Outlier detection for generic time series
In this case, "generic" being the entire gauntlet of macroeconomic time-series that private and government statistical offices put out.
Some background - I recently started working at a data provider ...
2
votes
6answers
398 views
How to assess effect of intervention in one state versus another using annual case fatality rate?
I am a beginner in statistics with just basic knowledge. I have these data: cases, deaths and CFR (Case Fatality Rate-deaths per 100 cases) of a disease for 17 years (1994-2010) from 2 neighbouring ...
2
votes
3answers
1k views
How to identify transfer functions in a time series regression forecasting model?
I am trying to build a time series regression forecasting model for an outcome variable, in dollar amount, in terms of other predictors/input variables and autocorrelated errors. This kind of model ...
8
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2answers
1k views
Good Introductions to Time Series (with R)
I am currently collecting data for an experiment into psychosocial characteristics associated with the experience of pain. As part of this, I am collecting GSR and BP measurements electronically from ...
6
votes
2answers
987 views
Computing correlation (and the significance of said correlation) between a pair of time series
I have two time series S, and T. they have the same frequency and the same length.
I would like to calculate (using R), the correlation between this pair (i.e. S and T), and also be able to calculate ...
7
votes
1answer
844 views
Time series clustering
I have many time series in this format 1 column in which I have date (d/m/yr) format and many columns that represent different time series like here:
...
4
votes
3answers
344 views
Forecasting time series based on a behavior of other one
Apologies for this vague and unclear question, I have no background in statistics.
I have two vectors of time series data, covering a six month period. The data is in daily intervals (except for ...
7
votes
1answer
1k views
Detect changes in time series
I came across a picture of an application prototype that finds significant changes ("trends" - not spikes/outliers) in traffic data:
I want to write a program (Java, optionally R) that is able to ...
5
votes
0answers
141 views
Updating classification probability in logistic regression through time
I am building a predictive model that forecasts a student's probability of success at the end of a term. I’m specifically interested in whether the student succeeds or fails, where success is usually ...
5
votes
1answer
740 views
Finding coefficients for VECM + exogenous variables
I want to extend the standard VECM form:
Δx[t] = δ0 + ... + Π x[t-1] + Φ1 Δx[t-1] + Φ1 Δx[t-2] + ... + ε
to include exogenous variables (i.e. variables that are participant in describing the ...
2
votes
1answer
235 views
Tools to detect jumps in a linear time series
I have a financial time series that has a linear down trend, but sometimes a jump happens (see image below).
What statistical methods can I use to detect these jumps as early as possible?
2
votes
2answers
722 views
Correlating volume timeseries
Consider the following graph:
The red line (left axis) describes the trading volume of a certain stock. The blue line (right axis) describes the twitter message volume for that stock. For instance, ...
1
vote
1answer
550 views
Reproducing ARIMA model outside R
I've got an ARIMA(1,1,4) model using external regressor with acceptable output but I'm not able to reproduce it outside the R.
this is the result for the model:
...
5
votes
4answers
3k views
How to perform pooled cross-sectional time series analysis?
For 86 companies and for 103 days, I have collected (i) tweets (variable hbVol) about each company and (ii) pageviews for the corporate wikipedia page (...
3
votes
1answer
328 views
Cannibalization of product sales
I am trying to determine the rate of cannibalization of product sales
for A with product B. I am using ~ 2 years of daily sales data
for product A and then ~8 months of data for product B. That is, ...
3
votes
2answers
108 views
What test should I use to determine if a policy change had a statistically significant impact on website registrations?
A client's website was operating under a certain policy for membership sign ups for over a year. At the start of October 2012 the client implemented a new policy for sign ups that was supposed to ...
3
votes
2answers
782 views
Non-Correlated errors from Generalized Least Square model (GLS)
As a financial institution, we often run into analysis of time series data. A lot of times we end up doing regression using time series variables. As this happens, we often encounter residuals with ...
2
votes
2answers
266 views
Time series Modelling - Forecasting for weekly incidents
I am new to R. I am trying to apply forecasting model Time Series (TS) Model
as follows:
Plotting original data,
Simple Moving Average,
Auto correction(AC), Partial AC, Differencing of TS etc ...
2
votes
2answers
719 views
Help with the Ljung-Box test for time independence of residuals
I fit a simple linear model y = bX to a data set today, and that produced 24 residuals (I have 24 data points, one for each year from 1984-2007). I would like to test the time-independence of the ...
3
votes
3answers
100 views
Handle leap seconds in time series data
I am trying to figure out how to handle time series data.
Initially, I thought it was self-evident (for my purposes) to only allow non-overlapping data blocks. (I.e., non-overlapping, time wise.)
...
3
votes
1answer
627 views
PACF manual calculation
I am trying to replicate the calculation that SAS and SPSS do for the partial autocorrelation function (PACF). In SAS it is produced through Proc Arima. The PACF values are the coefficients of an ...
2
votes
1answer
341 views
Arima model giving high forecast values
I have some models built with the auto.arima function from the forecast package. I'm modeling a variable called 'natural efluent ...
2
votes
1answer
1k views
How to find local peaks/valleys in a series of data?
Here is my experiment:
I am using the findPeaks function in the quantmod package:
I want to detect "local" peaks within a tolerance 5, i.e. the first locations ...
1
vote
2answers
456 views
Moving-average model error terms
This is a basic question on Box-Jenkins MA models. As I understand it, an MA model is basically a linear regression of time-series values $Y$ against previous error terms $e_t,..., e_{t-n}$. That is, ...
1
vote
1answer
290 views
How to the predict the number of daily visitors in six months' time based on the past three?
I do not know anything about statistics. I am a software engineer.
I had a question in my mind and I think here is the place to get my answer.
Suppose that I have data for 3 months. The data shows ...
1
vote
2answers
2k views
Whether a AR(P) process is stationary or not?
In practice, how to evaluate whether a AR(P) process is stationary or not?
How to determine the order for the AR and MA model?
0
votes
3answers
243 views
Effect of moving average parameter on variability and variance of demand
Consider an MA(1) process, $d_{t}=e_{t}-\Theta e_{t-1}$, when $d_t$ is the demand at time $t$ and $e_t$ is error term and $\Theta$ is moving average parameter. Now if $\Theta$ equal to zero so we have ...
26
votes
6answers
925 views
Pitfalls in time series analysis
I am just starting out self-learning in time series analysis. I've noticed that there are a number of potential pitfalls that aren't applicable to general statistics. So, building on What are common ...
10
votes
5answers
642 views
When to use multiple models for prediction?
This is a fairly general question:
I have typically found that using multiple different models outperforms one model when trying to predict a time series out of sample. Are there any good papers ...
35
votes
4answers
1k views
Do we have a problem of “pity upvotes”?
I know, this may sound like it is off-topic, but hear me out.
At Stack Overflow and here we get votes on posts, this is all stored in a tabular form.
E.g.:
post id voter id vote type ...
