Time series are data observed over time (either in continuous time or at discrete time periods).

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11
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What is a white noise process?

What is the best way of defining white noise process so it is intuitive and easy to understand?
5
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1answer
753 views

How can I effectively summarize and visualize time series of employee activities?

I am managing many people entering data into a database. I have a log of user, date, time, table, and action that each person makes: ...
2
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1answer
511 views

Aggregating results from Arima runs R

/edit: To clarify: The mtable function from the memisc package does exactly what I need, but unfortunately does not work with arima models. Similar to this question: I have multiple Arima models, ...
6
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1answer
4k views

Simulation of ARIMA (1,1,0) series

I have fitted the ARIMA models to the original time series, and the best model is ARIMA(1,1,0). Now I want to simulate the series from that model. I wrote the simple AR(1) model, but I couldn't ...
28
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5answers
4k 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 ...
0
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2answers
790 views

Trend detection quantitative models [closed]

What are the best quantitative models for trend detection? I.e. market trend.
1
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1answer
172 views

Objective measure of relaxation time towards equilibrium for a time series

I have several time series (generated from a numerical model) that go through an initial stage of spinup, followed by a period of dynamic equilibrium, that presumably exists for all times beyond the ...
4
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1answer
185 views

How should I deal with features with time related values in Bayesian network?

I would like to apply Bayesian network on some data. However, some of the variables are related to time. E.g. Number of time he/she visit library. As the value can be defined as Total number of ...
10
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1answer
428 views

Predicting long-memory processes

I'm working with a two-state process with $x_t$ in $\{1, -1\}$ for $t = 1, 2, \ldots$ The autocorrelation function is indicative of a process with long-memory, i.e. it displays a power law decay with ...
3
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3answers
693 views

A “systematic” part of a random time series component?

I've seen at least 3 sources on time series* state that the component of a series that is variously called random, stochastic, or noise (something clearly separate from any deterministic, patterned ...
16
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3answers
1k views

Logistic Regression and Dataset Structure

I am hoping that I can ask this question the correct way. I have access to play-by-play data, so it's more of an issue with best approach and constructing the data properly. What I am looking to do ...
9
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1answer
665 views

What temporal resolution for time series significance test?

I need some guidance on the appropriate level of pooling to use for difference of means tests on time series data. I am concerned about temporal and sacrificial pseudo-replication, which seem to be ...
2
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1answer
320 views

What types of analysis are appropriate for demographic time series data?

Let us say we have some demographic time series data which tells us how many hours people spend in front of a computer screen each day, grouped by age and gender: ...
7
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3answers
3k views

Predicting from a simple linear model with lags in R

I have a dataset that I want to fit a simple linear model to, but I want to include the lag of the dependent variable as one of the regressors. Then I want to predict future values of this time series ...
4
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2answers
269 views

Modeling vacancy rate

I have 100 geographical regions in a country. For each region the total number of houses and the number of vacant houses have been collected yearly over 20 years. I have also some other economic ...
7
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2answers
2k 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 ...
15
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5answers
4k 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 ...
1
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1answer
1k views

Lagged Exogenous Variables in VECM with R

Looking to estimate a VARX(p,q) type VECM in R if possible. I'd like to estimate a VECM with p lags (lags relative to the level, not diff of the vars) on the ...
7
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1answer
231 views

Merging spatial and temporal clusters

I've items that have a geo-spatial position and a temporal origin. For both dimensions, I build clusters so far. I'm now in search of a way to merge this different clusters forming spatio-temporal ...
11
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4answers
5k views

Simple linear model with autocorrelated errors in R

How do I fit a linear model with autocorrelated errors in R? In stata I would use the prais command, but I can't find an R equivalent...
12
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7answers
15k 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, ...
3
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1answer
235 views

Arranging hourly data for several years

I have hourly data for a variable for several years. I want to analyse each month separately. How do I arrange the data for the same month of different years? For example, suppose I have Jan 1997, ...
5
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1answer
337 views

Non-informative priors for the AR(1) model

I have a question about the AR(1) model. Expressed mathematically as: $$ Z_{t} = \rho Z_{t-1} + \epsilon_{t}, t=1,..,T$$ $$ \epsilon_{t} \sim iid \ N(0,1) $$ My question is about the ...
14
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4answers
9k views

When to log transform a time series before fitting an ARIMA model

I have previously used forecast pro to forecast univariate time series, but am switching my workflow over to R. The forecast package for R contains a lot of useful functions, but one thing it doesn't ...
7
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1answer
2k views

Combining auto.arima() and ets() from the forecast package

I've been using the ets() and auto.arima() functions from the forecast package to forecast a large number of univariate time series. I've been using the following function to choose between the 2 ...
3
votes
2answers
593 views

Threshold models and flu epidemic recognition

I'm fooling around with threshold time series models. While I was digging through what others have done, I ran across the CDC's site for flu data. http://www.cdc.gov/flu/weekly/ About 1/3 of the ...
11
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3answers
2k 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 ...
8
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2answers
4k views

Subsetting R time series vectors

I have a time series and I want to subset it while keeping it as a time series, preserving the start, end, and frequency. For example, let's say I have a time series: ...
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1answer
358 views

Low-pass Filter

I collected some data with an instruments with 1Hz sampling clock, now I want to low-pass filter the data to separate the mean and fluctuation part (Reynolds decomposition). How can I design a ...
4
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2answers
2k views

Time series cross section forecasting with R

I have a (I suspect) simple question. I have time series cross section data on voting behaviour in the Council of the European Union (the monthly number of yes, no and abstentions for each member ...
5
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1answer
125 views

Predicting a semi-deterministic process

Say I have a process that gives me 3 outputs: $O^1$, $O^2$ and $O^3$. The outputs are generated from a semi-deterministic process, i.e. there is a deterministic component in the outputs, along with a ...
9
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2answers
4k 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 ...
1
vote
1answer
522 views

Burn-in period for random walk

We are trying to make simulation experiment involving a common stochastic trend, that is described by the random walk (or $I(1)$ process) $Y_t = Y_{t-1} + \varepsilon_t$, where innovations ...
7
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3answers
707 views

Annotating graphs in R

This is more of a "how to use R" question than an actual hardcore statistics question, but I think the concentration of R masters here makes this a good forum for it. I'm refreshing a time series ...
2
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4answers
4k views

Is there any library like LOESS or ARIMA in Java/C# or Python?

I try to implement a time series data analysis project, but I have to do in Java, C# or Python, is there any good libary such like LOESS, ARIMA in R you can recommend? Many thanks
1
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1answer
164 views

Multiplicative unobservable component in state space model

I'm new here and wondering if anyone could give me some hints on how to estimate the time varying coefficient and state variable together. Here is my model: observation equation: $Y(t)= A(t)X(t)+ ...
11
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2answers
456 views

Interrater reliability for events in a time series with uncertainty about event time

I have multiple independent coders who are trying to identify events in a time series -- in this case, watching video of face-to-face conversation and looking for particular nonverbal behaviors (e.g., ...
9
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2answers
429 views

Incremental learning for LOESS time series model

I am currently working on some time series data, I know I can use LOESS/ARIMA model. The data is written to a vector whose length is 1000, which is a queue, updating every 15 minutes, Thus the ...
4
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2answers
1k views

DLM results looking wonky

I am teaching myself DLM's using R's dlm package and have two strange results. I am modeling a time series using three combined elements: a trend (...
1
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1answer
174 views

Removing macro-level time variance

The title might be a bit misleading. Unfortunately statistics is not my area of forte, so gentle guidance along the right path is much appreciated. That said, here's my problem: I'm working on ...
7
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3answers
2k views

How to re-sample an XTS time series in R?

I have an irregularly spaced XTS time series (with POSIXct values as index type). How can I build a new time series sampled at ...
0
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2answers
1k views

Moving return of exponential moving average — choice of alpha

I have a time series with an exponential moving average and I want to calculate a moving return of the EMA over the last m periods (something like a smoothed moving return). Let's say: Y(t) is the ...
4
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1answer
2k views

Getting started with time series in R

With some great help from this forum, I have been able to get up and running with some basic time series analysis in R. Right now, my needs are mostly univariate time series. Here is my question: I ...
6
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2answers
501 views

Resources for learning about spurious time series regression

"Spurious regression" (in the context of time series) and associated terms like unit root tests are something I've heard a lot about, but never understood. Why/when, intuitively, does it occur? (I ...
0
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1answer
2k views

Starting out with forecast package in R

I am new to forecasting in R and am trying to automatically fit an ARIMA model to what I believe is a univariate dataset. ...
5
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4answers
1k views

Determining trend significance in a time series

I have some time series data and want to test for the existence of and estimate the parameters of a linear trend in a dependent variable w.r.t. time, i.e. time is my independent variable. The time ...
3
votes
1answer
186 views

In a linear regression whose components can also be broken down, is it better to do multi-layered regression, or flatten to final components?

Consider a series like CPI (inflation), which I know is composed of a series of component prices (e.g. meat prices, grain prices, non-food prices, etc.), which in turn are also composed of a series of ...
5
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2answers
333 views

Developing a statistical test to ascertain better “fit”

In a data set with thousands of data points, I am testing different short-term and longer term data outputs based on 5 rolling data points all the way to 100 rolling data points (which each value ...
3
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2answers
777 views

Rewriting AR model in State-Space form

How can I rewrite an AR(p) model in state-space form? Max(p)=5 and I want to use Kalman Predictor.
4
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1answer
993 views

Confidence interval based on time series

I have a timeseries of data which was gathered by driving a car around randomly. One data point was gathered every minute and each data point is either "Yes" or "No". Yes = temperature is above a ...