Autocorrelation is the correlation of a series of data with itself at some lag. This is an important topic particularly in the analysis of time-series data.

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Autocorrelated residuals in pooled panel model

I have found several questions dealing with autocorrelattion and panel data, however I am not sure if the answers are applicable to my data/problem. I apologize in advance for possibly posting a ...
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Print significant auto-correlation values in R [on hold]

If I do an autocorrelation test in R (using function acf), I get a great graph, and the horizontal lines show the cutoff of significance. Function ...
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32 views

Cross-correlation of two autocorrelated signals (removing autocorrelation with ARIMA)

I want to get the cross-correlation of two time series x and y in R. I have calculated an ARIMA model, and I can get the ...
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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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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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15 views

Dirichlet multivariable regression with temporal autocorrelation?

BACKGROUND: I have some animal behaviour data. The time allocated by a group of animals to different behaviours per minute was recorded repeatedly until the end of the experiment. Therefore, I have ...
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19 views

showing the autocorrelation fn of a moving avg q MA(q) time series

I am struggling with a math problem set question and just wanting some pointers: I have this a stationary time series (MA(h)) that satisfies this equation below and has the sigma^2 below $x_t=(u_t + ...
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1answer
17 views

HAC standard error or missing ARMA terms

In the context of regressions, it seems a convention that the HAC estimator should be applied when the residual is serially correlated. But isn't the presence of residual autocorrelations an ...
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1answer
20 views

Cross-correlation gives autocorrelation in R?

I am not very familiar with cross-correlation analysis. I am analysing a large number of "paired" time series. For each pair, I am doing a ccf in R. I read in other posts that the horizontal line ...
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37 views

Influence of HAC estimates to p-value of t-test

I have a linear regression model and because of heteroskedasticity or autocorrrelation I use HAC (Newey-West) estimates. This influences also p-values of significance t-tests of estimated coefficients ...
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75 views

Correcting autocorrelation with MA in a regression

I would need some advice on a multivariate regression problem. I am running regressions with macroeconomic data at first difference and using a AR(1) as regressor to correct autocorrelation (it makes ...
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47 views

Is this “strong correlation” definition valid?

This page defines a a "strong correlation" using a formula that combines a standard correlation measure with lag-1 autocorrelation measures. I've never seen a definition of correlation like this ...
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12 views

Interpretation of ACF and PACF [duplicate]

How to interpret the ACF and PACF plots on top right and left? I have tried to look at different sites but am not sure.
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44 views

R: finding spatial patterns in rasters (Moran's I etc)

i'm not really experienced in spatial stats yet, but i'm growing into it. I basically want to ascertain if certain values in a raster are a) autocorrelated and b) are more likely to exist in a ...
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52 views

Mitigate autocorrelation in time series with AR(2) process

I have a dataframe with 4000 companies and I have calculated a liquidity measure of each of the company in the dataframe. Liquidity is highly persistent. And my analysis shows that in these indiviual ...
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35 views

Autocorrelation lme R

I am seeking advice on how to effectively eliminate autocorrelation from a linear mixed model. My experimental design and explanation of fixed and random factors can be found here from an earlier ...
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1answer
24 views

Portmanteau test results R

When reading a VAR model tutorial I was confused by the below excerpt on the Portmanteau test for autocorrelation. My questions are: 1) How does one interpret the results of the below demonstration? ...
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3answers
52 views

Is it possible to generate data for stochastic process with specific distribution and autocorrelation?

It seems though that there is a disconnect between constructing paths of a stochastic process with both a specific distribution and autocorrelation. It seems like you can have either one property or ...
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34 views

Time Series and Testing Auto Correlation

Consider the following asset pricing model: $$RET_t=0.621+1.414(M_t)+0.732(HML_t)+1.9349(SMB_t)+0.250(RET_{t-1}) $$ $$(0.077) \hspace{5mm} (4.141) \hspace{5mm} (3.242) \hspace{5mm} (3.294) ...
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1answer
38 views

Relationship between probability distribution and correlation [closed]

I'm unsure of the precise relationship between a probability distribution and correlation, in particular autocorrelation. What exactly is an autocorrelated probability distribution? It seems like ...
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1answer
177 views

Does using lagged independent variables makes sense?

While it seems quite common to calculate a lagged version of the dependent variable and to use it on the right hand side of a model (e.g., autoregressive models), I have rarely seen that lagged ...
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31 views

Arbitrary spatial autocorrelation

A spatial autoregressive model includes a spatial lag of the dependent variable. $$ y = \rho W y + x\beta$$ Where $W$ describes the spatial relationship between elements of the model. I have heard ...
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20 views

heteroscedastic time series in SAS autoreg - white noise matter?

I normally work with categorical outcomes, so a lot of this is new to me. Attempting to model monthly interrupted time-series in proc autoreg. There were 11 intervention changes of varying potency ...
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20 views

Find the equilibrium point and its variance in stochastic data?

I have some data of the form I need to find the point where it starts reaching equilibrium (as I can see from the graph around 1000 iteration) and how much fluctuating the data points are. Is there ...
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40 views

Can my data be described as a random walk or not?

I'm trying to figure out whether the observed "time series" can be described as a random walk or not. Unfortunately a major problem regarding my data is in time intervals: Problem: Time ...
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2answers
32 views

Ljung Box test chi square distribution

I want to prove the following statement: Under $H_{0}$ the test statistic $Q=n(n+2)$ $\sum \limits_{k=1}^h \frac{\hat{p}_{k}^2}{n-k}$ follows a $\chi ^2(h)$ chi-squared distribution with $h$ degrees ...
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7 views

interpretation of autocorrelation

I have some random vectors with different directions and sizes. I calculate autocorrelation function and I plot it. It would be an exponential function but it is not.how can I interpret this plot?
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27 views

Residual autocorrelation and forecasting

My residuals are autocorrelated. Will this be a problem if I want to use the time series to do forecasting?
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35 views

Test of significance between autocorrelation coefficients for two time series

I have a time series measured at monthly intervals, and I want to determine if the first half of the series is less persistent than the second half of the series. My initial thinking was to the ...
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17 views

Estimation of covariance matrix using 2D power spectral density

1. What I need : A full Covariance matrix, $\Sigma$ $(N^2 \times N^2)$, in order to apply my algorithm. PSD - Power Spectral Density (and not positive semi-definite) 2. What I have: a) An image N ...
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20 views

Autocorrelated cyclical component of Hodrick-Prescott filter

I run a linear regression of the cyclical component of the Hodrick-Prescott filter and I obtained the following graph of the autocorrelation and partial autocorrelation of the residuals: My ...
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14 views

Network Autocorrelation using R // sna package and lnam

I'm currently working on my Thesis in Statistics about Network Autocorrelation Models. I've used the package 'sna' in R for Social Network Analysis in order to obtain some graphical result. Inside the ...
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10 views

Serial correlation misunderstanding

A consequence of having serial correlation in a model is downward bias of the standard errors of the estimated coefficients. This means that t-scores are inflated or overestimated. However, does the ...
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18 views

Single lagged PACF spike: Why select MA term in model and not AR term?

I'm trying to understand the specific choice of model in an example in the book "Applied Econometric Time Series" by Enders, chapter 2 ("Stationary time-series models"), section 7 ("Sample ...
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13 views

Adding lags to AR model does not seem to reduce residual autocorrelation

I'm fairly new this stuff so please bear with me. I'm trying to model operating margins. I believe the time plot to be stationary so my first thought was to model Margin(t) = b0 + b1*margin(t-1). The ...
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21 views

Adjusting for spatial autocorrelation

I have a data set on sand martin population sizes along a stretch of river over 40 years. The river is split into sections and the number of birds per section was counted. I have been trying to ...
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1answer
26 views

Durbin-watson test for autocorrelation

Also Durbin Watson test showed to be: Durbin-Watson D=1.672, Number of Obs=171, 1st order autocorrelation=0.162 Do I have autocorrelation problem?
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1answer
28 views

Modelling a time-series with lags

I have a data set with 200 predictors and 700 observations. It is a regular time series, so 700 days in my case. I want to experiment with lagged variables, which I will create manually and save as ...
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23 views

SAS Heteroscedasticity and Autocorrelation

I did a white test for heteroscedasticity problem and got the following: DF=27, Chi-Square=33.91, Pr>ChiSq=0.1688 Do I have heteroscedasticity? How do I know? Also Durbin Watson test showed to be: ...
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Compute autocorrelation in a trace of covariances matrices sampled by MCMC

Imagine that we sample a covariance matrix from a Wishart distribution by MCMC. At every iteration, we get a new sample matrix $S_i$ from the Wishart distribution. Q: Given the trace that contains ...
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1answer
43 views

How to interpret ACF and PACF?

Can you please tell me what should be the values of ACF and PACF from the graphs I have attached? I think it should be ($p=0$, $d=1$, $q=3$). I have differenced the data once so $d=1$ and there ...
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2answers
73 views

Specify order of ARIMA model using autocorrelogram

How can I, using the correlograms above, specify the orders of the ARIMA model? These are the pac an ac of the differenced time series. Using AIC and BIC, I can't seem te find a proper model. ...
3
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1answer
46 views

Measuring dependency of subsequent points from Markov chain

The question is about stimulating different type of species (coded 1-10) based on given species frequencies, and other parameters (eg. mean of normally distributed mass and ratio) using gibbs ...
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2answers
93 views

How to determine the critical values of ACF?

I have a sample of 1000 data points and I used it as the training sample to forecast with Timeseries. My lecture suggested me comparing the ACF with its critical values (upper and lower) numerically ...
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11 views

can fixed effects be controlled for in panel corrected standard errors(XTPCSE)

I am doing a panel data analysis. I have serial correlation and groupwise hetroskedasticity in my model and if I don't control for time effects (year effect) then I have contemporaneous correlation ...
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14 views

Autocovariance function example

For example I have my time-series 4.6,4.2,5.1,5.4,8.0 means is 5.46 With R acf(v,plot=FALSE) ...
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5 views

Infinite server queue with self-similar traffic

We are looking for results on: Queue length distribution for infinite server queue under long range dependent self similar traffic. We find results for infinite server queues under Markovian ...
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1answer
29 views

Does Auto-correlation cause AR(p) model?

This is the autocorrelation case. $y_{t}=X_{t}B+u_{t}$ where $u_{t}=\rho u_{t-1}+e_{t},$ $e_{t}$ is iid From this autocorrelated disturbances, I might be able to say $y_{t}=\gamma ...
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How to determine the variance of an autocorrelation estimator?

In reference to the hint: the calculated expected value from problem 2 was found to be: Where the variables changed slightly due to where the image was found, however l = h in the question, and r ...
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40 views

Am I doing this right - choosing the order of p and q for an ARMA model (time series)?

I have a time series and have to come up with the ARMA(p,q) model that fits best to the data. (I have read ARIMA model identification, which was helpful, but doesn't completely resolve my question). ...