Tagged Questions

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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Interpretation of glmmPQL() spatial autocorrelation output

I am modeling binominal data with random effects and spatial autocorrelation using MASS::glmmPQL(). Plotting the residual semivariogram of a model fit without ...
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Time Series Data Mining and Correlation guidance [on hold]

Introduction Editing this post to clarify what I am asking. This is a bit of a vague question to begin with. I am not asking if this particular statistics method with these variables will cause this ...
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Covariance function and autocovariance function of a fractional Brownian motion?

What is the difference between covariance function and autocovariance function of a fractional Brownian motion? Page 6: Eq 1.6 /1.7 http://www.columbia.edu/~ad3217/fbm/thesisold.pdf Second: How can ...
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Regression model on small samples y and x measured over time

I want to measure the direction and strength of relationship between Urban growth and GDP using a regression model (8 observations and can't get more). Both are measured over time, so there is auto-...
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Forecasting: residuals from seasonal decomposition appears to be highly auto-corelated, why?

I am using a publicly available data Kaggle: Rossmann Store Sales and trying to forecast sales. I am using Python. My timeseries is stationary, confirmed via the Dickey-Fuller test. However, I wanted ...
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Is there a nonparametric test available in R to analyze serial dependencies for short time series?

I am developing a small web application with R and the Shiny-package to conduct easy analysis of single-case time series data. For this purpose, I need a nonparametric test that allows to analyze ...
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Is autocorrelation not worth addressing with small N?

Consider a simple regression context in which there is a small set of response values, $Y$, and corresponding dates, $X$. (For simplicity, we can assume the dates are equally spaced.) We would like ...
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Correlation with seasonal data

I've got 5+ years of data, with multiple observations per week. I'd like to understand if there is a correlation between my dependent and independent variables. The catch is that I know this data is ...
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Why is my semivariance so high?

I am using variograms checking for spatial autocorrelation in a resiudal pattern produced by a GLMM-NB. In theory, the semivariance should be bounded between 0 and 1 (that´s what I think at least as I ...
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How many lags should be considered when testing for serial correlation in the error terms?

In a time-series OLS regression of daily stock returns on a set of explanatory variables I want to test whether the error terms are auto-correlated before I decide to use Newey-West standard errors (...
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Analyzing series of events, controlling lengths

(Excuse me for terminological problems. After I tried to find the solution, I started looking for at least the right names for the concepts I use, but I failed, as the simple descriptions I tried to ...
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Breusch–Godfrey test under heteroskedasticity

Do I need to account for heteroskedasticity when performing the (vector) AR1-2 test? The Autocorrelation (AR) 1-2 test is defined as follows - often reffered to as the Breusch–Godfrey test (Wiki link)...
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How to control serially correlated independent variables?

I'm interested in studying the impact of one variable (e.g., R&D expense at year T) on future firm performance (e.g., Sales in year T+5), I know it's incorrect to specify the following model: ...
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Heteroscedasticity,Autocorrelation,Chow test

Can a Chow test be run on a dataset which has autocorrelation and/or heteroscedasticity? Will the F-stat give accurate results?
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What do you think of this correlogram?

do you think this weekly data is stationary? Unit-root test indicates rejects null of non-stationary (rejects null of unit root). Thanks for your input.
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Testing for spatial autocorrelation in residuals - time series

I have a ~25 year dataset of annual count of species abundance in several traps. Within a year, the abundance in a trap might be dependent on the abundance in another trap. I want to test the effect ...
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How would I interpret this correlogram from EViews?

This is a correlogram on stock market data generated in EViews. How would I interpret it, in regards to AR and MA? Also, why are all my p-values 0? I would assume they wouldn't be as stock markets ...
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Controlling for autocorrelation in crosscorrelation

I have two timeseries ...
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Incorporating autocorrelation into forecasts

I have a time series $x_{t}$ which is an AR(1) process with a constant term, e.g. $x_{t} = c + \phi x_{t-1} + \epsilon_{t}$ How can I incorporate information about the autocorrelation of $x_{t}$ ...
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Using Mantel test to check spatial independence in time series?

For my analysis in biology, I want to study the effects of several factors (climate, cultivated area...) on insect dynamics and phenology. For that, I have data of insect captures from several traps ...
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Does autocorrelation imply stationarity?

Let \begin{aligned} y_t &= a + bx_t + u_t, \\ u_t &= \phi u_{t-1} + e_t \end{aligned} where $e_t$ follows a White Noise process. Let Breusch-Godfrey LM test statistic be strictly ...
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Checking spatial autocorrelation by plotting residuals?

For my analysis in biology, I want to study the effects of several factors (climate, cultivated area...) on insect dynamics and phenology. For that, I have data of insect captures from several traps ...