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

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Forecast encompassing test for cointegrated time series

I am forecasting an integrated time series variable $y_t$. I have two competing forecasts, $f^1_t:=f^1_{t|t-h}$ and $f^2_t:=f^2_{t|t-h}$. I would like to test whether $f^1_t$ forecast-encompasses ...
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3 views

LSSVM Prediction using LS-SVMLab toolbox v1.8

I'm trying to forecast a time series of air passengers using LSSVM with the help of the LS-SVMLab toolbox v1.8 from http://www.esat.kuleuven.be/sista/lssvmlab/, specifically the NARX model function. ...
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11 views

Statistics of performance

I have done some testing on the performance of a method. Basically, there are 4 materials I can use. Each will give me a different amount of results in a different time frame. I used these four ...
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1answer
230 views

How do I compare date-ranges from a time series?

I have a time series which contains monthly readings for air pollution in a city. The seasonality from this time series has been removed. Given two date ranges, for example Jan-Aug 2008 and Jan-Aug ...
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14 views

Similarities between Pade approximations and ARMA(p,q) in time series [on hold]

I am wondering if someone would mind explaining how Pade approximations in calculus and ARMA(p,q) in time series are similar.
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5 views

Modelling Reflexivity with a Time Series Model

I'm new to this forum so hi to everyone! I would like to find a time series model that is capable of modelling two time series with following properties: 1) consider time series X and Y. X is ...
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2answers
1k views

How to extract long run and short run coefficients from ARDL (UECM) estimates?

I have estimated ARDL(UECM) in eviews but I dont know how to specify or extract the long run an short run estimates/coefficienst? what is the standard procedure to do so?
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2answers
260 views

Regression analysis for more than one categorical variable in time series

I have a time series data for shipment with following variables: Year: 2008, 2009, 2010, 2011, 2012, 2013 Month: jan, feb, ..., dec Number of ordering days Shipment Volume I want to know the ...
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1answer
15 views

Time series regression coefficient interpretation with differenced independent variable

I'm working on a project on time series regression. The independent variable was non stationary so I took first differences to stationarize it. Now when I regress it against the dependent variable the ...
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2answers
23 views

Dynamical time warping for dynamical system classification

I am trying to find a way to classify and segment a large set of time series that each individually describe a dynamical system. I wanted to know if the following idea for doing so is a feasible ...
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13 views

X-13 Seasonal Adjustment trading day peak in regarima residual

I have a time series of air passengers with a total of 143 monthly observations. Having done the seasonal adjustment using X-13-ARIMA-SEATS, the final diagnostics seem to suggest that the seasonal ...
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0answers
9 views

time-series analysis / forecast compared to real planning (controlling) departments?

The following case study: Planning and forecasting in a volatile setting by Amy Wheeler, Nina Weitkamp, Patrick Berlekamp, Johannes Brauer, Andreas Faatz and Hans-Ulrich Holst, published in Rob ...
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26 views

how to show that a decrease is significant in a time series data

I have 2 time series - one from the 1990s and one from 2000s. (The data is each decade is not continuous - meaning in the 1990s, I have data from 1991, 1993, 1996, 1997 and for 2000s, only from 2002 ...
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2answers
457 views

R seasonal time series

I use the decompose function in R and come up with the 3 components of my monthly time series (trend, seasonal and random). If I ...
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28 views

Vector autoregression: many variables (10), short sample (100)

Suppose there are ten observation sites along the road. A, B, C, D, E, F, G, H, I, J. We obtain data at each site once in a day, in this order. That is, first go to the site A at 9:00a.m., and when ...
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1answer
27 views

VAR/VECM/ARDL optimal lag selection

Question 1: Is it necessary to consider AIC and the BIC criteria when selecting the lag for a VAR, VECM or ARDL model OR can I use something else? Example: Can I pick 12 lags because the model simply ...
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8 views

determine confidence bounds for turning points with RAPS

I'm computing the Rescaled Adjusted Partial Sums (RAPS) of a time series to identify periods of change in the data. A description of this method can be found in: Garbrecht, J. and Fernandez, G.P. ...
2
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1answer
367 views

ARIMA, adjustments and intervention analysis

I have very little knowledge of time-series analysis (despite my stat master - didn't do anything else than an introductory course) but now I'm facing a statistical problem whose answer is this very ...
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1answer
575 views

Forward Filtering Backwards Sampling (FFBS) and Look-Ahead Bias

Assumptions / Context: Let's assume that I have data that can be modeled as a dynamic linear model. To estimate the parameters (e.g., covariance matrix of the state/system equation), I use a Gibbs ...
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2answers
45 views

Classifying time-series similarity - what variable should I train on?

I have ~10,000 time series, each with 65 time points. I'm interested in classifying each pair of time series as "similar" or "not similar". Here's an example of two similar (left) and not similar time ...
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1answer
137 views

How to compare 3D accelerometer data in time series?

I'm trying to find similarity between two time series of 3D accelerometer data: Just by looking at the graphs I can tell that red-circled parts looks pretty similar to me, but I would like to get ...
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16 views

Measuring promotion baseline smoothing

I am trying to estimate promo effectiveness for a retail product. To do this I have taken monthly quantity sold data for the product. My question is - Is it logical to model the sales baseline (sales ...
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10 views

Jittery sampling of jittery events - what to prioritize

Stat beginner with a practical problem. In an industrial application, I'm sampling a repetitive production process, to generate a histogram of the cycle time. The cycle time of course varies somewhat ...
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2answers
70 views

Time series forecasting with many predictors

Suppose I want to forecast a time series $y$ using its own lags and a large set of potential candidate predictors $X$. The model could be specified as follows: $$y_t = a + \rho \cdot y_{t-1} + \beta ...
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Time series and images : difference and terminology

A time series is an ordered collection of random variables. Considering a one-dimensional time series $A_i = {a_{i1},a_{i2},\ldots,a_{it}}$ where $t$ denotes the time index. So, the time series is a ...
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17 views

Time series pattern match in large datasets

I want to find in a time series pattern that look similar to a predifined one. At the moment I am using DTW to do this and it works well. But now I want to use it for larger datasets like finding a ...
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23 views

A time series which cannot be made stationary

I have a series of data points, of days between successive earthquakes. I am trying to model time between earthquakes, in order to predict waiting times. Using Minitab I have tried differencing, ...
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45 views

What statistical models / approaches can I use to estimate missing hourly values?

My dataset consists of hourly values by weekday across several sites, where the sites vary by spatial location and by other common characteristics, such as type, or 'cafe,' 'restaurant,' and 'bar.' ...
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1answer
265 views

How to determine “trendiness” of a time series

I'd like to be able to compare two timeseries as to their level of "trendiness" to determine which trends better. For example, assume two stocks, Google and IBM. Would like to understand approaches to ...
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9 views

References for Combine Seasonal Period in Seasonal Time Series

I'm in a middle writing my thesis. I got confused for find the references which said period of seasonal could be chosen from the small period which already containing another periods. Here is my ...
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2answers
42 views

Estimating unconditional variance in time series

Consider a time series process with a well-defined, finite unconditional variance. Given a realization of the process (a time series) and a model for it, there are at least two ways of estimating the ...
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1answer
22 views

Algorithm to determine a point in time series data, after which probability of increase in value is very low

I am working with dataset which contains number of movie tickets sold per day. This is basically a count of total number of tickets sold, for a particular movie, for each day after its release date. I ...
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1answer
17 views

Interpretation of level, trend and seasonal indices in Holt-Winters exponential smoothing

I am trying to learn Holt-Winters exponential smoothing. In the algorithm there are three indices involved (level, trend, ...
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1answer
263 views

Time series with multiple subjects and multiple variables in R

I'm having trouble finding a time series technique to deal with a data set I am working on. It contains multiple subjects and multiple variables, not all of which will likely be part of the time ...
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19 views

Google Trends: Stitching 90 day periods of daily data together

Google Trends lets you see the amount of researches made on for a term on google during a set period of time, normalized between 0 and 100 (depending on the highest value in that period). I would like ...
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24 views

PCA to decorrelate and classify timeseries

I have a labeled dataset where each subject belongs to one of two classes A or B, with A ...
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23 views

Rules of integrated series and balanced regressions

Background There are various rules of linear combinations of integrated series. Let's just consider the $I(0)$ and $I(1)$ cases. For example, if $x_{t} \sim I(1)$, $y_{t} \sim I(0)$, then $ax_{t} + ...
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1answer
41 views

Predicting time series using `arima` or `fitlm` in Matlab?

I have 6 sequences (time series); they all belong to the same variable. I divide each sequence in two parts having 80% and leaving the last 20% for validation. I am doing the analysis and modelling in ...
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26 views

Testing for white noise for non stationary time series

I could not find a question where testing for white noise for non strick stationary non parametric time series is adressed. Per definition white noise is stationary. But finding a series that is ...
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2answers
24 views

Modelling effect of advertisement on sales with ARMAX

I am trying to model the effect of advertisement on sales in Stata. The data is weekly and there are around 150 observations. I started by applying an ARMAX(1,0,1) model with the following exogenous ...
4
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1answer
413 views

How to map a trajectory to a vector?

I have a series of data points in this form (timestamp, lat, long) for a set of users. Each user has a trajectory when he travels from point A to point B. There might be any number of points from A to ...
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2answers
55 views

Can we identify ARIMA model without looking at ACF and PACF plot?

Can we identify ARIMA($p,d,q$) model without looking at the ACF and PACF plots? I am trying to write a generalized R programme for fitting time series models. We may find out the orders $p$, $d$ and ...
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16 views

Suggestions for Neural Network Structure for Time-Series prediction with constant covariates

I've been working on a time series prediction problem and wondered if someone has run across a similar problem structure & can make a suggestion on how to structure the training data, network, or ...
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10 views

R: How to pack the seasonal components of time-series to an array-like structure? [on hold]

I am trying to calculate the decomposition of 34 time-series to study the similarity of seasonal components, as explains this this tutorial I start from a CSV that, after some transformations and ...
4
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2answers
101 views

Strictly Stationary Time Series with Infinite Moments

Can someone give me an example of a strictly stationary time series with infinite moments? I am reading a book on Time Series by Wayne A. Fuller where it is said that a strictly stationary time series ...
5
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1answer
6k views

“Frequency” value for seconds/minutes intervals data in R

I'm using R(3.1.1), and ARIMA models for forecasting. I would like to know what should be the "frequency" parameter, which is assigned in the ts() function, if im ...
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11 views

Residual Not Normal for Model Seasonal Time Series in R

I got a problem when choose the model for forecasting with time series. I'm in a middle writing my Thesis. My data have a seasonal pattern so, i tried use this model ...
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16 views

Sum of the AR coefficients and First Order Autocorrelation Coefficient

I'm working with quarterly inflation, usually a AR(4) and I want to obtain different measures of persistence, that are: 1. the sum of the AR coefficients Σα 2. First Order Correlation Coefficient, ...
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1answer
2k views

How accurate is F test in panel data

I heard that the F-test is to advice you whether to use fixed effects or pooled OLS. However, I didn't find any details about it in books. Only in a very few studies. What is the hypothesis of the ...