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

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Dealing with different time series data in Machine Learning

I am trying to create a stock market model based on fundamental variables for the US economy. I am using R. Some of the variables I am looking to include are: GDP, Unemployment Rate, Initial Claims, ...
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37 views

How do I calculate the distribution of number of events in the busiest period?

I've got an estimate of the number of site visitors I'll see in a 1 hour period clicking email links in a large email campaign. I need to make sure I've got the required server capacity. That means ...
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225 views

Quantile regression

I have a question regarding quantile regression. Supposing that I have 10000 observations with one response variable and several predictor variables in a dataset collected each year over several ...
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18 views

Causality in microeconometrics versus granger causality in time-series econometrics

I understand the causality as used in microeconomics(in particular IV or regression discontinuity design) and also the Granger causality as used in time-series econometrics. How do I relate one with ...
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Help for planning a neuroscience experiment

I'm new here. I am planning a neuroscience experiment. I will be measuring brain signals from about twenty subjects. I will present the subjects four different kinds of stimuli. After all the data ...
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6 views

Dynamic conditional correlation DCC subscrip invalid function return error

I have two series as standardized residuals generated from arch(1) garch(1): ...
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23 views

How to compare two different clustering approaches?

I'm making a project connected with identifying the dynamics of sales. My database concerns 26 weeks (so equally in 26 time-series observations) after launching the product, 126 time-series=126 ...
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16 views

Standard deviation of several measurements with uncertainties

I have two 2 hours of GPS data with a sampling rate of 1 Hz (7200 measurements). The data are given in the form (X, X_sigma, Y, Y_sigma, Z, Z_sigma), where N_sigma is the measurement uncertainty. ...
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18 views

Aggregation of correlated variables

I've been trying to aggregate correlated time series, by using Alexander's proposal that you can see here: http://bit.ly/1hIPwiI. Her proposal to find a random variable $Y=\sum_{i=1}^N X_i$, where ...
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Observed versus Synthetic data

I am looking for studies that compare different spatial interpolation methods for observed data. However I am looking for studies that have also compared observed with generated synthetic data. For ...
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61 views

Markov Switching Forecast. How can I derive this?

Consider the autoregressive model, $\left[ \begin{array}{l} y^{\ast}_t\\ x_t^{\ast} \end{array} \right] = \left[ \begin{array}{l} a_{11}\\ a_{21} \end{array} \begin{array}{l} a_{12}\\ ...
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42 views

GARCH modelling

Is this simplistic way of describing GARCH processes correct: Future prices do not depend on previous prices per se, but rather on the previous variance. If this is incorrect, is there a model ...
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10 views

Construct matrix of stacked variables in VAR regression

I am trying to NOT use packages for the estimation of models in order to have a deeper understanding of how things work. Currently, I am trying to estimate a VAR(1) (vector autoregression of first ...
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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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134 views

ZScore threshold and low values time-series

Example of z-score computation: 1 - E.g. Time-series: [0, 0, 0, 0, 1] Current: 1 Mean: 0.2 Std: 0.44721 Z = (1 - 0.2) / 0.44721 ~= 1.7888 2 - E.g. ...
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524 views

Simple interrupted time series analysis

I have a weekly time series representing costs for a cohort. I want to tell whether an intervention on the cohort (we can assume it happened in a single week) has decreased costs for the cohort. I ...
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130 views

What's a stationary VAR?

What is a stationary VAR (vector autoregression)? Can a VAR with non-stationary variables be stationary? How do you test whether a VAR is stationary or non-stationary? (Example in ...
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66 views

Diagnostic for VAR model. non normal

I have some problem about my model. my model is based on VAR. (vector auto-.) well, I've tested ARCH test, BG test(autocorrelation p) and jarque.bera.test. Model is stable. Also I got good result for ...
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How to know if a time series is stationary or non-stationary?

I am using R, I searched on Google and learnt that kpss.test(), PP.test(), and adf.test() ...
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42 views

Statistical significance in time series and sub-series

So, when I did first year stats in undergrad, we did an experiment where we tampered with a bunch of coins, to see if it would cause a statistical difference in the results. This is a graph of the ...
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55 views

Time series trend

I have a time series which has a very strong upward trend for the first half, then very strong downward for the second half and finishes pretty much back where it started. Should I split the data in ...
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76 views

Regression on time series and its segment series

I want to test whether segment series explains anything in additional to the full series. Let's say y and ts_full are time series with same length. And I divide ts_full to 3 non-overlapping sub time ...
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17 views

Calculate first difference by group in R [migrated]

I was wondering if someone could help me calculate the first difference of a score by group. I know it should be a simple process but for some reason I'm having trouble doing it..... yikes Here's an ...
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Trying a multivariate analyses on time series (with R)

I got measures of one variable (that behaves as a time series) for different conditions (some quantitatives, but mostly are qualitatives). For example, this is a "fake" representative plot of this ...
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How to examine the change of event sequences

Let's assume we have a sequence of events $x_1, x_2, ...,x_n$ and each event can be described as a categorical variable from domain $\{A, B, C...\}$. The time interval between two consecutive events ...
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29 views

When an ARMAX model is stationary? Why stationarity or invertibility is needed?

Let $y_t$ a stochastic process and $\tau_t$ presents the time duration between the $t$ and $t-1$ event.The ARMA(p,q,r) with exogenous variables is defined as: $$ y_t = \varepsilon_t + ...
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How to do Simulation for Time Series Model using SPSS

I am totally new to SPSS. I have a question on Simulation. Can we apply simulation for time series model using SPSS? Thanks in advance.
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37 views

Understanding factor potentials in PyMC

I'm trying to understand factor potentials from the PyMC documentation, but need some help on the implementation piece--or it may turn out that I am misunderstanding how potentials work altogether. ...
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30 views

Augmented Dickey Fuller output conflicting in Stata

I am required to perform unit root testing on a given time series. The output obtained in Stata is somewhat confusing me. To the best of my knowledge I am obtaining two conflicting results, Stata ...
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50 views

Time series forecasts of appointments with pre-registration

Looking for some tips and ideas. I get a list every day of the number of appointments for each day for the next two weeks for a clinic. I have quite good history of these list, and the actual number ...
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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 ...
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116 views

Determining the best correlated time series

Before asking, I read similar questions, but none of them lead to satisfying answers for my specific interest. I want to homogenize a climate time series of precipitation of the Dominican Republic ...
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37 views

What does “AR(p) filtered series” mean?

I guess this means that omitting some variables in a certain interval, say, $(x_1, x_2, x_3, x_4, x_5) \to (x_1, x_5)$ in AR(4) model. Is it right? Or does this means eliminating autocorrelations ...
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116 views

Time series as cross-sectional data

I have time series, for example, gdp and unemployment(unemp), freq= 4. What if I interpret it as cross-sectional data and do cross-sectional analysis instead of ...
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What are differences between the terms “time series analysis” and “longitudinal data analysis”

When talking about longitudinal data, we may refer to data collected over time from the same subject / study unit repeatedly, thus there are correlations for the observations within the same subject, ...
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182 views

Data mining techniques in R for advertising and sales data

I would like to apply one or more data mining techniques to a dataset, in order to see the effect advertising has on sales. I am working from this dataset. It has 36 consecutive entries of monthly ...
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Which steps have to be done before fitting logistic curve to time-series?

I want to cluster time-series concerning sales of products. In the database I have 26weeks after launching each products and units sold each week. One of the method of clustering is to cluster ...
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39 views

Entropy estimation for a symbol sequence

I am looking for an R-implementation of the Lempel-Ziv data compression algorithm, to estimate the source entropy of a time-series consisting of a sequence of symbols. Rather than simply measuring ...
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Longitudinal data: time series, repeated measures, or something else?

In plain English: I have a multiple regression or ANOVA model but the response variable for each individual is a curvilinear function of time. How can I tell which of the right-hand-side ...
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SVAR Model with Short run restrictions

I am currently working on implementing SVAR model in an economic analysis. I have 10 variables in my analysis and currently struggling to incorporate the short run ...
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95 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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34 views

How to test for wide-sense stationarity with only one sample path of the process?

I have a univariate time series consisting of 70,000 observations (power consumption of a building) over equal time increments (15 minutes). How do I check whether this realization is wide-sense ...
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Knowing the level of aggregate processes, how to get the levels of constituents?

I have a bunch of component processes $y_{it}$, where $i=1..n$. I can build reasonable time series models $y_{it}=f_i(y_{i,s<t},X_t)$, where $X_t$ - exogenous variables. These could be ARIMAX ...
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65 views

Does it make sense to use dynamic time warping when clustering time series that all have the same length and sampling interval?

Comparing Euclidean distances with dynamic time warping (DTW): Will Euclidean distance perform better than DTW when clustering time series that all have the same length and sampling interval? Are ...
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67 views

Aggregating samples for clustering time series

I want to cluster a set of 512 time series. The time series have sampling intervals of 1 day over a time period of 5 years. Thus, each time series consists of about 1800 samples. However, many of the ...
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60 views

Time series analysis: Determine if trend is deterministic fluctuating/stable or stochastic

I am analysing sales data of certain products and need to determine if the demand trend is deterministic fluctuating or deterministic stable or stochastic. How do I do that in R / what approach is ...
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85 views

How to obtain the model behind a simulator?

I am looking for an useful statistical approach or analysis tool in order to understand the data obtained from an aeroelastic simulator of wind turbine dynamics. In this case, the simulation provides ...
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50 views

Warning message in auto.arima

I am using auto.arima() for prediction, and getting the following warning message. I want to know if I can ignore this warning message or if I should be worried. ...
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30 views

Error Calculating MVN Likelihood of Time Series with AR(1) Errors in R

I'm having trouble calculating the likelihood of a time series with AR(1) errors. I am generating my covariance matrix according to page 2 of (http://cran.r-project.org/doc/contri...regression.pdf), ...
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Statistical method to find capacity limits?

Im analyzing time-series to detect when the y-value is so flat that one can assume there is an underlying factor limiting y from being higher. Is there a methodology or statistical discipline that do ...