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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Adding a history flag variable to panel data with possible auto-correlation
I have a pretty basic question. A client has given me a data set with tens of thousands of subjects. Each subject has from one to about ten separate records. These records cover successive ...
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2answers
100 views
Evaluation of Autocorr/Part Autocorr values
I am practicing MA and AR modelling by using autocorrelation and partial autocorrelation values. My data is in the image below; I can see that only at lag 12 there is a value that might be considered ...
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3answers
879 views
AR(1) selection using sample ACF-PACF
The following graph shows the ACF (sample autocorrelation function) and PACF (partial autocorrelation function) of the residuals in a linear regression. There is a sinusoidal decay in the ACF and two ...
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1answer
99 views
AcF and Stationarity
Very often in time series literature, it is remarked that if a series is non-stationary the AcF will decrease to zero very slowly while the opposite occurs for a stationary series.
What's the basis ...
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1answer
534 views
Interpreting seasonality with ACF and PACF
I have a dataset where empirical intuition say I should expect a weekly seasonality (i.e., the behavior in saturday and sunday is different from the rest of the week). Should this premise be true, ...
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1answer
778 views
Measuring correlation or dependence between two data sets
Is there any statistical test or measure to evaluation the degree of correlation or dependence between two sets of data-points ?
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53 views
finding x intercept from a set of values
I have run an ACF on a function in R and it returns:
Autocorrelations of series ‘sine.curve’, by lag
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1answer
156 views
Random walk or not?
I'm trying to understand whether the observed time series can be described as a random walk or not.
When I check autocorrelations of the differences, none of the autocorrelation bars for the ...
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2answers
269 views
Top-Down or Bottom-Up Approach for demand forecasting
I have 5000 SKUs which all of them are highly positive autocorrelated, to get the item level forecast for all5000 SKUs (disaggregate forecast) which approach can provide more accurate forecasts, BU ...
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117 views
White noise for level, log and log differences data sets
I am using eviews 7 and I have 3 data sets for DAX stock market index: level (dax), log (ldax), and log differences (dldax). I need to check whether the error terms of these data sets are white noise ...
2
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0answers
438 views
Newey-West t-statistics
I have a time-series which is autocorrelated by construction, and might be heteroscedastic. I have calculated the sample mean of this time-series, and would like to calculate the t-statistic ...
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2answers
132 views
Quantile regression and heteroscedasticity/autocorrelation
I hear it said [1] that QR makes no distribution assumptions about its error term.
Question 1: Does this mean that heteroscedastic and serially correlated disturbances do not effect the ...
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1answer
91 views
Contradictory Results in autocorrelation tests
I have a time-series model, with stationary variables. Testing for outocorrelation hasn't been easy:
- a can't calculate DW stat because of my small number of observations;
- the GB test indicates ...
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1answer
181 views
How to model binary dependent data with temporal autocorrelation?
I am trying to model annual tree nut production using climate predictors.
The nut data (dependent) is a binary timeseries (0,1 - representing unsuccessful and successful nut production), with one ...
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0answers
68 views
Calculating R-squared values from a semivariogram
I have some spatially autocorrelated vegetation data, and would like to know the how well tree size measured at one location can predict tree size in plots 100m away.
I've made a semivariogram of ...
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1answer
205 views
Auto-correlation of Random numbers
Is saying random numbers are independent equivalent to saying random numbers are auto-correlated in simulation. I am using Auto-correlation method in simulation.
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41 views
Computing autocorrelation from weighted samples
Suppose I've used Metropolis-Hastings to get samples from a candidate distribution, then associated with each an importance weight. (Perhaps the target distribution was too rowdy to use MH directly, ...
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1answer
525 views
Box-Ljung test on white noise series
I generate this data in R:
set.seed(111)
ds=rnorm(1000)
When I perform Box-Ljung test to test the independency:
...
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1answer
326 views
Newey West standard errors give me more significance
I had a time series model with 5 time series variables and it's a model that's reputed in the literature for having autocorrelation problems. Why when I use standard OLS var-covar matrix only 2 ...
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80 views
(Quantile regression) AR(1) variable in the design matrix
I'm not doing a pure QAR (quantile auto regression) but I do have a lagged dependent variable (AR(1)) as a predictor. I'm using the quantreg package in ...
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1answer
189 views
(Quantile regression) Which standard error for heteroscedasticity & serial correlation
I have heteroscedastic and autocorrelated residuals in my multivariate quantile regression model.
What's the quantile regression standard error estimator that's robust to this? Something hopefully ...
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1answer
396 views
Linear Regression and Spatial-Autocorrelation
I want to predict Tree Heights in a certain area using some variable obtained through remote sensing. Like approximate Biomass, etc. I want to first use a linear regression (I know it's not the best ...
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87 views
Singular covariance matrix and Spatially-correlated random effects [closed]
I'm interested in incorporating spatially-correlated random effects into my model to explicitly account for between-observation spatial autocorrelation, such that spatial autocorrelation decreases ...
17
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3answers
786 views
Why does including latitude and longitude in a GAM account for spatial autocorrelation?
I have produced generalized additive models for deforestation. To account for spatial-autocorrelation, I have included latitude and longitude as a smoothed, interaction term (i.e. s(x,y)).
I've based ...
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1answer
217 views
Is there an intuitive interpretation of a negative variogram “nugget” value?
A variogram plots the variance of the difference between sample pairs on a field (any dimensionality) against spatial separation (the "lag") of those samples.
The extrapolation from observed ...
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4answers
3k views
How to perform pooled cross-sectional time series analysis?
For 86 companies and for 103 days, I have collected (i) tweets (variable hbVol) about each company and (ii) pageviews for the corporate wikipedia page (...
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2answers
677 views
How to perform Prais-Winsten autoregression in SPSS 16? [closed]
When performing a linear regression on my dataset, Durbin-Watson was very low (0.276). I found a tutorial online that suggested performing an Prais-Winston autocorrelation. The tutoral came with ...
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73 views
Can you use a spline function of the spatial coordinates to control for spatial autocorrelation? [duplicate]
Possible Duplicate:
Why does including latitude and longitude in a GAM account for spatial autocorrelation?
I am interested in the effect of a predictor vector $X_i$ on a binary outcome ...
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2answers
331 views
Skewness, kurtosis and normality of a time series
I have a sample size of $21$ with $496$ observations.Can I presume an approximately normal distribution,and use a $t$-test to compare the difference in means, and difference in various financial ...
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2answers
2k views
What to do with very low Durbin-Watson?
For 100 companies, I have collected (i) tweets and (ii) corporate website pageviews for 148 ...
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0answers
91 views
Discriminant analysis with random effects
Is it possible to do discriminant analysis with random effects?
Is there an R package for this?
Context:
I have habitat use data for two species of frogs from radio telemetry, but nested within ...
3
votes
2answers
299 views
Regression to obtain autocorrelation measure (AR(1))
This is not homework. I am a frequent user on math.stackexchange, but I am learning a bit about time series models and came across this example. Any ideas would be greatly appreciated.
A linear ...
3
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0answers
93 views
Making new variable instead of correcting for temporal autocorrelation in a GLMM. Is it a valid alternative?
I am doing some forest disturbance research, in which the aim is to predict the probabilities of wind damage occurrence in forest stands of different site (altitude, slope steepness) and stand ...
3
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2answers
1k views
Most appropriate way to make a time series stationary? (i.e. remove serial correlation?)
So I have this data set of 56 users with 52 weeks worth of weekly average data for blood pressure and exercise level recordings. I would like to use change point analysis ...
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3answers
408 views
Automated procedure for selecting subset of data points w/ strongest correlation?
Is there some standard procedure (such that one might cite it as a reference) for selecting the subset of data points from a larger pool with the strongest correlation (along just two dimensions)?
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1answer
184 views
Modeling a spatial trend by regression with the $(x,y)$ coordinates as predictors
I plan to include coordinates as covariates in the regression equation in order to adjust for the spatial trend that exists in the data. After that, I want to test residuals on spatial autocorrelation ...
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129 views
Some questions about VAR-models, $\Phi$-matrix-coefficients and partial-(auto-)correlations
There is an abundance of literature about VAR-models, which teaches how to test preconditions, specify and estimate VAR-models for stationary and also cointegrated time-series.
However, I'm still a ...
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3answers
356 views
Autocorrelation from multiple time series samples
I have multiple samples of a time series (for example, the time series might be minutely samples from 12am to 3pm, and I have that for ten different days) and I'd like to compute the autocorrelation ...
3
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1answer
262 views
Testing periodogram “peaks”: sine-like wave or AR/MA/ARMA noise?
I'm performing an harmonic fit to data I know (from physical constraints) come from a periodic source of the form
$$\sum_j^M \sum_i^N a_{i,j}\sin(2\pi f_it)+b_{i,j}\cos(2\pi f_it)$$
using the ...
5
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1answer
220 views
Why autocovariances could fully characterise a time series?
I read from textbook that 'Autocovariance can fully charaterise the time series' joint distribution', I do not fully understand the connection between covariance and joint distribution here. Please ...
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1answer
183 views
Moving average signal confidence
Please advise how best to approach the following;
I have a trend following trading signal comprising a trailing simple moving average over n data points. The data is stationary. Currently i ...
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0answers
164 views
How to find and describe regularities in a distribution of interarrival times of a recurring event?
I want to see if there are regularities in interarrival times of a recurring event in discrete time. I know that I can fit distributions to the interarrival time distribution, but are there other ...
3
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3answers
756 views
Creating auto-correlated random values in R
We are trying to create auto-correlated random values which will be used as timeseries. We have no existing data we refer to and just want to create the vector from scratch.
On the one hand we need ...
3
votes
3answers
325 views
Does autocorrelation cause bias in the regression parameters in piecewise regression?
In simple linear regression problems, autocorrelated residuals are supposed not to result in biased estimates for the regression parameters. Can the same be said for piecewise regression?
Suppose I ...
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0answers
52 views
How to plot a correlogram [duplicate]
Possible Duplicate:
Computing and plotting a correlogram
I have spatial data for a grid of size 20x20. I wanted to know how I can plot a correlogram to see how much the data are correlated ...
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2answers
177 views
Analyze spatial correlation from a plot [closed]
I want to know how random variables at a certain geographic location are correlated spatially. Lets say I have a certain function z depending on the spatial locations of the points. If I plot this z ...
3
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1answer
1k views
What is the difference between serial correlation and having a unit root?
I may be mixing up my time series and non time series concepts, but what is the difference between a regression model that exhibits serial correlation and a model that exhibits a unit root?
In ...
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3answers
305 views
Good reference on sample autocorrelation?
I'm not a statistician but I'm writing my thesis on mathematical finance and I think it would be neat to have a short section about independence of stock returns. I need to get better understanding ...
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2answers
418 views
How to reduce autocorrelation in Metropolis algorithm?
I've been using a Metropolis/Gibbs sampler combination to generate a joint density for some parameters(it is a hierarchical model, with $y_i\sim Poisson(\lambda_i)$, $\lambda_i\sim ...
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1answer
93 views
“autocorrelation” of nominal variable
I have data on patients attendance of a series of sessions of counseling. At each session, a patient could be A, S or D. Each patient has data for 12 sessions, and there are ~100 patients.
I am ...
