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

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Interpreting the result of decomposing time series

I don't have a lot of experience working with time series data. Now I have a 3 year, monthly data for several entities (you can think about them as different stores), that I would like to do some ...
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1answer
53 views

How to test predictive power of ARIMA model

Once I've fitted an ARIMA model (by choosing, say, the one with the lowest AIC), how can I go about gauging how effective it is at forecasting a given financial time series? Should I somehow ...
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37 views

orthogonalized impulse response's contradictory forms in a VAR(p) model

I have so far discovered three different ways of utilizing the Cholesky decomposition for calculating the OIRFs of a VAR(k). The different methods seem contradictory so I would like some input on ...
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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, ...
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1answer
24 views

How to use SVM to do time series prediction?

I want to know how to use SVM to do time series prediction? what the differences of input vecvtor X of our model between time-series prediction and standard kernelized regression problem?
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7 views

Is series cointegrated if residual is stationary under time-varying coefficient regression?

Traditionally, if $x_t$ and $y_t$ are both $I(1)$, they are cointegrated when there exists some linear combination $z_t=y_t-$$\gamma$ $x_t$ such that $z_t$ is stationary or $I(0)$. My question is if ...
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1answer
24 views

What's the best (Google chart) visualisation for displaying sparse timeline data across thousands of “columns”

I am trying to visualise a sparse dataset but am finding it hard to fit it into the standard categories of charts. I'm a developer building with Google Charts and I really want to stick with that ...
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1answer
27 views

What is the meaning characterizing a model as “conditional mean”

I've been going through time series material of late, trying to re-invent myself as a practitioner in the field. Until I got to the point of actually trying to Matlab some models, I had never run ...
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25 views

Best way to account for time lags in logistic regression (GLM or GLMM)

I am trying to determine the best, most conservative way to account of time lags in a logistic regression type analysis (a generalized linear model with or without mixed effects). I am working with ...
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14 views

Difference between autocovariance and autocorrelation [on hold]

I read from a book when i read about Yule-Walker estimation that "autocorrelation has nicer properties than autocovariance".. can any one tell me why please
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14 views

Need an effective way to show distribution changes over time and outlier reoccurence

Does anyone have suggestions on the best way to approach this problem? I have a large dataset (over 200k+ per day) in a MySQL database, that consists of a single record per user per day with a ...
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0answers
23 views

Finding the optimal combination of independent variables for a constrained dependent variable

I'm currently working on power plant time series data and my main objective is finding out the optimal combination of independent variables which would keep "SO2 concentration (dependent variable) ...
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1answer
35 views

What is the long run variance?

How is long run variance in the realm of time series analysis defined? I understand it is utilized in the case there is a correlation structure in the data. So our stochastic process would not be a ...
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3answers
3k views

Is AR(1) a Markov process?

Is AR(1) process such as $y_t=\rho y_{t-1}+\varepsilon_t$ a Markov process? If it is, then VAR(1) is the vector version of Markov process?
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1answer
16 views

Seasonal component in irregular time series

Is it possible to identify seasonality in a Time Series that is irregular? I am currently working with a time series that is being periodically constructed (via crawling), but these crawled ...
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1answer
28 views

How to add time dummies in a regression?

I would be grateful if someone teaches me how to use time dummies in a regression to capture the effect of introducing a law. I am doing a study on reforms by assessing the pre and post effect of a ...
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1answer
22 views

How do I obtain the “Anomaly series” of a time series?

I have a time series of the Sea Surface Temperature (SST) of the Caribean Sea and I have to obtain the anomalies of that time series. ...
2
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1answer
45 views

Breusch-Pagan Test for ARIMA Model in R

I am testing my model using the Breusch-Pagan Test, but have not been able to find anything online regarding how to calculate it for an ARIMA Model. My AR1 Model is: ...
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0answers
7 views

How can I find Matching between a data set with given data set groups

I have a variability data new one, I would like to find the matching between given data set with group of data sets, which one among the data sets group has matched with the new data set. eg: A, B, ...
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30 views

Curve fitting in R

I had 4 groups of data (in color 1 to 4) and one group is the data for one day, so I had 4 days of data. I was trying to fit a line which describes the pattern of theses lines (oscillating pattern) ...
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1answer
317 views

Statistical comparison of two signals

I need to develop an algorithm that will compare two signals and generate some metric(s) to describe changes between them. Signal processing and analysis isn’t my strong point so I would appreciate ...
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0answers
20 views

Time series forecasting use SVM

I am trying to set-up a python code for forecasting a time-series, using SVM libraries of scikit-learn. My data contains X values at a day interval for the last one years, and I need to predict y for ...
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0answers
14 views

Longer forecasting with one-step-ahead model

It is totally a noob question but I cannot find any explanation on the subject. Suppose I build a forecasting system for time series $x$, using as inputs $[x_{t-n},...,x_t]$ to predict the next ...
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1answer
93 views

SV model estimation in R using tsbugs

I have been trying to estimate the basic stochastic volatility model using OpenBUGS via R and at an stage of the following command. Please can you comment for the ...
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0answers
8 views

On Estimating the spectral density with a weighted sum of the sample covariances

I am new to estimating the spectral density and would like a reference that demonstrates that taking a weighted sum of the sample covariances of a sequence of covariance stationary random variables ...
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3answers
174 views

find the point at which the curve significantly shoots up

so this is getting a little complex for me and hope someone can help me out. I do not have a mathematical background. I have a time series of daily rainfall for 50 years for a particular location. ...
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15 views

deletion diagnostics for time series

I'm following a tutorial on time series regression, which discusses diagnosis through selective deletion of data across the entire set of predictors, one observation at a time: ...
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0answers
24 views

How to find AIC, BIC values in Johansen cointegration test in R software? [on hold]

In order to take the best lag for Johansen cointegration test (trace) we have to take the lag with minimum AIC and BIC values, right? In R, I have used the syntax ...
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1answer
33 views

Estimation of a VECM model

I am attending a time series econometrics course and I am working on VECM models. We have learnt that to estimate a VECM model we should use Engle-Granger two-step procedure but I have not understood ...
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21 views

Differing frequencies for time series ts() function in R

I understand the frequency argument of the ts function in R is set to work for monthly, quarterly, yearly data, etc. In my case, ...
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1answer
38 views

A quick question about time series forecasting

I have collected daily sales data X(t) and Y(t) over two different areas . Total sales Z(t) ...
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1answer
44 views

Understanding the Durbin Watson test

The test statistic for the Durbin Watson test can range from 0-4 from what I have gathered. Now the lower limit of 0 makes sense considering the test statistic consists of two summations which are ...
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1answer
130 views

Timeseries Analysis

I have the weekly time series data from 2011 to 2014 with 6 variables (Gross_Revenue, Attendence, Enrollmentcount etc.) and its having seasonality. I want forecast the Gross_Revnue for 2015 1st 15 ...
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1answer
35 views

Time Series Analysis using Fourier Technique

i need to perform "Time Series Analysis" using Fourier Analysis/Technique on temperature data of 17 years. Their are four columns in it "Years", "Months", "Days" and "Temperature in C". I need basic ...
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41 views

Bad results for R's auto.arima

I have a time series for sales data on a weekly and monthly basis. I tried using holt.winter and auto.arima. ...
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6 views

Hedge ratio formula

Help to clarify this fact. In the simplest case, in order to find the hedge ratio using a linear regression of the form: $S_t = \alpha + hF_t + \epsilon_t$, where $h$ is the hedge ratio or the slope ...
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11 views

Statistically test difference based on time series

Usually in statistical hypothesis testing, we randomly split some unit into treatment group and control group, and we test if there are difference between treatment group and control group based on a ...
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5answers
299 views

What algorithm should I use to detect anomalies on time-series?

Background I'm working in Network Operations Center, we monitor computer systems and their performance. One of the key metrics to monitor is a number of visitors\customers currently connected to our ...
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3answers
340 views

Regression of data that includes a date

I have a dataset that contains a few hundred transactions from a three suppliers operating in 100+ countries over a three year period. We've found that the country of sales is not a significant ...
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1answer
20 views

Starting-point of time-series influences regression?

I've used tslm() under the R-package fpp to analyse two time series, which seem similar: ...
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19 views

concept drift detection

I'm working on a project that involves concept drift detection for a time series. Are there any well-known techniques/methods/algorithms that are known to be effective for this sort of problem? ...
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1answer
307 views

Time Series Data Mining Library?

Can anyone recommend a library for time series data mining tasks other than predictive modeling and statistical analysis? There seem to be a number for these purposes (e.g., Gretl), but nothing for ...
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1answer
166 views

Nearly constant time series

I want to analyse temporal interactions of some time series by means of the Box-Jenkins approach to find out which time series are predictors of another one (with the help of prewhitening and ...
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13 views

Aggregated probability using irregularly-spaced time series data

I have dataset describing a group of animals' size and growth over 2 years. These particular animals grow in non-continuous growth steps and I wish to model the frequency of these growth steps during ...
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1answer
75 views

forecast(method ='arima') ; auto.arima() function, how to avoid forecast not in line with history?

I am working on an alogorithm in R to automatize a monthly forecast calculation. I am using, among others, the forecast(method='arima') function from the forecast package to calculate forecast. It is ...
2
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1answer
28 views

compare time series data with ODE simulation

The same experiment was performed for 4 different initial conditions $(j=1,2,3,4)$. For each initial condition, there were 3 repetition $(i=1,2,3)$ of the experiment. I have 4 sets of data: $X_{ij} = ...
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44 views

Cross Country Analysis Time Series

I'm pretty newbie in econometrics, I'm writing a research proposal, and I was wondering if you guys can give your opinion or some hints regarding an idea. My dependent variable is a measure of ...
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0answers
17 views

Tune a neural network and prevent overfitting

I'm using a neural network for the first time and I would like to know if I'm doing this right. I'm working with time series for 5 years, and in each year I have a total of 18 time series plus the ...
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3answers
257 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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2answers
263 views

Fit VAR model with unknown order in Matlab

I have a multivariate observed time series $Y_t$ and I want to find the best fitting VAR process for it. I have the econometric toolbox in Matlab and can use 'vgxvarx' if I pre-specify an order for ...