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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Variance-covariance matrix as the sum of variance covariance matrices

I have a variance-covariance matrix, $\mathrm{V}$. This allows me to take a vector, $x$ of independent random variables drawn from a known distribution, and induce a required variance-covariance ...
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1answer
53 views
+50

Binning method: looking for an example

I heard and read several times of the use of 'binning' methods to estimate the uncertainty and the auto-correlation time of a sample generated by MCMC but I can't find a textbook example of it being ...
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24 views

Library routine for rolling window lag 1 autocorrelation?

I am looking for a library routine that will calculate the lag 1 autocorrelation of a time series with a rolling window; meaning "slide a window of size N points along the time series, calculate the ...
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1answer
19 views

Residual autocorrelation versus lagged dependent variable

When modeling time series one has the possibility to (1) model the correlational structure of the error terms as e.g. an AR(1) process (2) include the lagged dependent variable as an explanatory ...
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2answers
72 views

Why is it desirable to have low auto-correlation in MCMC?

I keep reading about the need to check for autocorrelation in MCMC. Why is it important that the autocorrelation is low? What does it measure in the context of MCMC?
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48 views

Classical or robust variogram for incorporation into generalized linear model [migrated]

I'm modeling counts of organisms over time at eleven locations. I'd like to account for temporal autocorrelation in the counts, assuming it's present. As the data are not equally spaced in time, ...
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1answer
35 views

Is the Durbin-Watson test appropriate for count data

In determining if there is any serial correlation in a time series of count data, is the Durbin-Watson statistic or similar approaches appropriate? I ask this question because the dwtest implemented ...
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1answer
66 views

Getting Residuals to be White Noise

I'm on a time series project for an undergraduate course. For the project I'm trying to come up with an ARIMA model for the housing starts data set. ...
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1answer
54 views

Estimation of regression with autocorrelated errors

In a book it is written that, In regression work we typically assume that the observational errors are pairwise uncorrelated. But in most time series data , the successive residuals have tendency to ...
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17 views

Two-tailed test [duplicate]

In one-tailed test , we give our decision at $\alpha$ level of significant. But in two-tailed test , why do we give our decision at $2\alpha$ level of significant? Why do we not give the decision of ...
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1answer
48 views

Spatially auto-regressive two-stage model

I'm working on a project in which I use a 'Generalized Spatial Two-Stage Least Squares' model, mostly known as $y= X \beta + \lambda W y + u$ and $u = \rho M u + \epsilon_n$ where $y$ and $u$ are ...
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1answer
40 views

Durbin Watson test statistic

I applied the DW test to my regression model in R and I got a DW test statistic of 1.78 and a p-value of 2.2e-16 = 0. Does this mean there is no autocorrelation between the residuals because the ...
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30 views

Extremal serial dependence

As part of my analysis of heavy-tailed time series of company returns, I would like to check whether extreme returns exhibit serial dependence, i.e. if extreme events are followed by extreme events. ...
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33 views

ACF and PACF plot analysis

I am new to ARIMA, and I am trying to understand these lag plots. Are the following ACF and PACF suggesting that the lag of my time series is 4? If I am wrong, please help me understand these plots. ...
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0answers
16 views

how to deal with autocorrelation

My study is related to determinants of corporate liquidity and I am working on eviews. My model gives durbin watson stat value 0.89. after applying fixed effect estimation the value changes to 1.47. ...
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0answers
110 views

consequences of lagged dependent variables in panel data and how to deal with it?

I have some elementary problems understanding the consequences of using/adding a lagged dependent variable in my predictive model. I’m trying to predict values $Y_{i,t+\tau}$ for $\tau=1-3$ with: ...
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14 views

Methods for measuring snowball effects in a “complete” longitudinal dataset

I'm looking for ways to test for "cumulative advantage" effects in a longitudinal dataset (see image) I guess the data set is principally similar to this: http://www.caldercenter.org/whatis.cfm , ...
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1answer
108 views

Can First Differencing Cause Negative Serial Correlation

Ex. series, say stock prices 103 101 102 150 101 102 100 First differenced 2 1 48 -49 1 -2 Notice you could guess a very large negative number following the very large positive in the first ...
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22 views

Poisson autocorrelation function

I want to draw an autocorrelation function, call it, AC(tau) where tau is the offset in the autocorrelatin. The vector I'm feeding into the AC is the spike train of a neuron whose action potential ...
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13 views

Postestimation results after VAR analysis show autocorrelation in residuals

I'm performing a VAR analysis on news effects and S&P500 returns. Now, I specified the number of lags (5) according to Schwarze's Bayesian Information Criterion (SBIC) and ran some postestimation ...
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33 views

Testing significance of correlation between two autocorrelated series

Say I collected the shin bones of N different skeletons; they are all around 30cm long, and I measured different properties P1, P2, P3, P4 and P5 along these bones every 3mm (so I have 100 data points ...
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47 views

Which type of residuals to use for the Durbin-Watson test (autocorrelation)

I want to check if there is residual autocorrelation in my model and the test for this is the Durbin-Watson test. I am using R and my question is if it makes a difference which type of residuals one ...
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1answer
29 views

Autocorrelation of convolution integral

Work out the autocorrelation $r_Y(\tau) = E[Y(t)Y(t+\tau)]$ with $Y(t) = \int_{-\infty}^{\infty} h(t-u) x(u)$ and $X$ a WSS, ergodic process I always get: $h(t)* h(t+\tau) * r_X(\tau)$ (with $*$ ...
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72 views

Residual autocorrelation in Poisson (Neg.Bin) models - Durbin Watson test

I am running some Poisson (or Neg.Binomial depending on overdispersion) models and i want to check for residual autocorrelation due to the nature of the data (monthly cases). I am using R and i am ...
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63 views

Whitening Transformation using a Hadamard product Variance Matrix

I want to whiten a vector $X$ by transforming the variance-covariance matrix so the variance-covariance matrix of the transformed series will be the identity matrix $I$. $X$ is a time-series column ...
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12 views

Is lm.morantest valid on residuals from geeglm fit of binary data?

Is it valid to apply lm.morantest (in the package spdep) to test for spatial autocorrelation among residuals from a Generalized Explanatory Equation (geeglm in geepack) model fit of binary data? If ...
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1answer
30 views

Unexplained symmetry when computing Power Spectral Density of white noise

I'm trying to learn more about noise, power spectral density (PSD) and statistical variances. With regard this I'm trying to compute the power spectral density of white noise. However, when I do I get ...
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1answer
62 views

What is the difference between (universal) kriging and spatial autoregressive models?

As part of a course on missing observations in social/survey statistics I am trying to explore existing methods of predicting either point pattern or polygon data. I got quite confused by all the ...
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1answer
27 views

Correlation definition between two set

How can I define correlation between two set x and y: {$(x_1,y_1),(x_2,y_2),(x_3,y_3),...(x_n,y_n)$} Is this definition correct: ...
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1answer
32 views

Estimating auto-correlation with unequally spaced data

I'm working on a time series problem where the spacing between observations is usually 12 or 24 hours, but this is not guaranteed. I'd really like to estimate the auto-correlation function, and I've ...
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1answer
45 views

Bias of Panel Generalization of Durbin-Watson

I'm working with an unbalanced panel dataset. (Country-Time) of approximate dimensions H=100 individuals i and average time length over individuals $mean(T_i)\approx7.5$. And about n= 8 regressors ...
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24 views

Can time-invariant variables cause autocorrelation?

I am running a pooled OLS regression and Random effects regression. I have tested for autocorrelation for both methods. In the pooled OLS model I find serial correlation but for the RE model I find ...
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31 views

Why does this autocorrelation formula hold?

I have been unable to understand the highlighted subsection of David Kenny's Correlation and Causality, which I downloaded from Kenny's website.
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2answers
67 views

does a log transformation of the dependent variable affect autocorrelation?

I have panel data and have used the xtserial command in Stata to test whether there is autocorrelation. When I take the log of the dependent variable, the test shows that there is autocorrelation. ...
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1answer
72 views

How to interpret autocorrelation

I have calculated autocorrelation on time series data on the patterns of movement of a fish based on its positions: X (x.ts) and Y (...
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33 views

Sample autocovariance of Durbin–Watson test

I understand Durbin–Watson test, but I can't understand this sentence. I cannot prove it. The Durbin-Watson test statistics is asymptotically equivalent to (rootT*C), where C is the sample ...
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1answer
90 views

What causes a U shaped pattern in the spatial correlogram?

I've noticed in my own work this pattern when examining a spatial correlogram at varying distances a U-shaped pattern in the correlations emerges. More specifically, strong positive correlations at ...
2
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1answer
145 views

Autocorrelation of discrete time series

I am currently planning on calculating the autocorrelation for various lags given a time series. However, my elements of the time series are "discrete" and abstract classes; i.e., no integers. For ...
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35 views

How to test for autocorrelation with pooled OLS?

Wooldridge 2002 describes how to test for serial correlation in pooled OLS but I don´t get it when I have to use it in STATA. Does anyone know how to test for serial correlation after pooled ols? I ...
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59 views

Autocorrelation tests for time series VAR models

I have a VAR model in which I regress the monthly unemployment rate on itself lagged one month, the monthly GDP percent growth lagged by two months and two dummy variables. I am trying to test for the ...
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3answers
64 views

Model estimation using ACF and PACF [closed]

Can anyone help in model estimation ? The following are the ACF,PACF and the plot of the sample respectively.
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88 views

Autocorrelation, Durbin-Watson and non time-series data

I have a simple linear regression with age as independent variable and a cognitive scale as dependent variable. Each subject is present only once. As it is not time-series data and there is no ...
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66 views

Interpreting results of an Augmented Dickey-Fuller test

I am running the 3 models of the ADF (Augmented Dickey Fuller) test on a (ln total fertility rate) variable. The results: Intercept only: (lag difference = 0) at level; p-value for Z(t) = 0.9672. ...
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1answer
70 views

Using ACF or PACF to build an AR(p) model?

In my text, we're told to use PACF to find the order of MA(q) models and ACF to find the order of AR(p) models. But in a homework problem, the professor specifies the order of an AR(p) model using the ...
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2answers
307 views

Why is my idea about correlation wrong here?

Autocorrelation is defined as $\rho(\tau)=E((x_i-\mu)(x_{i+\tau}-\mu))/\sigma^2$ which should have a value between $\pm1$. However, what if both $x_i$ and $x_{i+\tau}$ are significantly larger than ...
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36 views

Understand the PACF Values in R / Correlation over 1

I have a basic problem with the pacf function in R. By applying this function to get the partial auto correlation functions of a time series, the values range in ...
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1answer
78 views

How to interpolate independent variable over five-year period?

I have panel data on income and population for the years 1990, 1995, 2000 and 2005. I would like to interpolate these two variables (both independent variables), so that I have data for every year ...
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20 views

Find correlating hashtags

I have a couple of user profiles, that contain hashtags like this: user1: #sports, #bike, #enduro, #racing, #mountainbike user2: #sports, #bike, #racing, #mountainbike, #mtb (...) userN: #mtb I ...
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1answer
67 views

Is ARMA(0,0) equivalent to white noise?

If the EACF of my TS suggests ARMA(0,0) and the Box-Ljung test does not suggest my TS has correlation, can I conclude that my TS is white noise or merely that there is no reason to suspect that it is ...
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22 views

Regression with t distributed autocorrelated errors

I am new, so please bear with me, until its correctly formulated: In short: I am doing simultaneous non-linear regression (parameter estimation) of two different parametric models to three different, ...