The autocorrelation tag has no wiki summary.
17
votes
3answers
701 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 ...
11
votes
3answers
397 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)?
...
10
votes
1answer
123 views
Two years of data describing occurence of violence- testing association with number of patients on ward
I have two years of data which looks basically like this:
Date ___ Violence Y/N? _ Number of patients
1/1/2008 ____ 0 __________ 11
2/1/2008 ____ 0 _________ 11
3/1/2008 _____1 ...
9
votes
3answers
2k views
Simple linear model with autocorrelated errors in R
How do I fit a linear model with autocorrelated errors in R? In stata I would use the prais command, but I can't find an R equivalent...
9
votes
2answers
2k views
Formula for autocorrelation in R vs. Excel
I am trying to figure out how R computes lag-k autocorrelation (apparently, it is the same formula used by Minitab and SAS), so that I can compare it to using Excel's CORREL function applied to the ...
9
votes
1answer
374 views
Predicting long-memory processes
I'm working with a two-state process with $x_t$ in $\{1, -1\}$ for $t = 1, 2, \ldots$
The autocorrelation function is indicative of a process with long-memory, i.e. it displays a power law decay with ...
8
votes
2answers
342 views
What's the deal with autocorrelation?
To preface this, I have a pretty deep mathematical background, but I've never really dealt with time series, or statistical modeling. So you don't have to be very gentle with me :)
I'm reading this ...
7
votes
3answers
7k views
How to test the autocorrelation of the residuals?
I have a matrix with two columns that have many prices (750).
In the image below I plotted the residuals of the follow linear regression:
...
7
votes
1answer
495 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, ...
7
votes
3answers
958 views
How to model zero inflated, over dispersed poisson time series?
I am trying to model weekly disease counts in 25 different regions within 1 country over a ten year period as influenced by temperature. The data is zero inflated and over dispersed.
I am most ...
7
votes
1answer
169 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 ...
7
votes
1answer
920 views
Using autocorrelation to find commonly occurring signal fragments
I have a sensor which is capturing accelerometer data as a person walks. What I'm interested in extracting is each signal fragment when a step is taken. The Z-axis is what is used since only one axis ...
6
votes
1answer
2k views
Calculate Newey-West standard errors without an lm object in R
I asked this question yesterday on StackOverflow, and got an answer, but we agreed that it seems a bit hackish and there may be a better way to look at it.
The question: I would like calculate the ...
6
votes
2answers
245 views
How can I compute regression for several longitudinal data sets (thus, with auto-correlated error)?
My actual project is a bit complicated, but I'll explain by analogy (which I hope facilitates response):
I have 3 substances, say water, motor oil, and ethanol. For each substance, I have 5 samples ...
6
votes
2answers
250 views
Measures of autocorrelation in categorical values of a Markov Chain?
Direct Question: Are there any measures of auto-correlation for a sequence of observations of an (unordered) categorical variable?
Background: I'm using MCMC to sample from a categorical variable ...
6
votes
1answer
737 views
Time series regression with overlapping data
I am seeing a regression model which is regressing Year-on-Year stock index returns on lagged (12 months) Year-on-Year returns of the same stock index, credit spread (difference between monthly mean ...
6
votes
2answers
480 views
Choice of weight function in Moran's I
I'm doing an autocorrelation analysis for a spatially distributed collection of observations. To perform my analysis, I am using Moran's I statistic.
My questions are: (1) What are the implications ...
6
votes
1answer
473 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:
...
6
votes
1answer
167 views
How to analyze GEE with unevenly spaced observations?
I am interested in using Generalized Estimating Equations (GEE) to model longitudinal count data. I recorded animal count observations on the same sites on many days but the spacing of the ...
6
votes
0answers
606 views
How to analyze longitudinal count data: accounting for temporal autocorrelation in GLMM?
Hello statistical gurus and R programming wizards,
I am interested in modeling animal captures as a function of environmental conditions and day of the year. As part of another study, I have counts ...
5
votes
2answers
1k views
Autocorrelation in the presence of non-stationarity?
Does the autocorrelation function have any meaning with a non-stationary time series?
The time series is generally assumed to be stationary before autocorrelation is used for Box and Jenkins modeling ...
5
votes
1answer
216 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 ...
5
votes
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 (...
5
votes
2answers
371 views
Can I trust a regression if variables are autocorrelated?
Both variables (dependent and independent) show autocorrelation effects. Data is time-series and stationary
When I run the regression residuals appear not to be correlated.
My Durbin-Watson statistic ...
5
votes
2answers
179 views
How to tell if residuals are autocorrelated from a graphic
When you do an OLS regression and plot the resulting residuals, how can you tell if the residuals are autocorrelated? I know there are tests for this (Durbin, Breusch-Godfrey) but I was wondering if ...
5
votes
2answers
1k views
Fitting multiple linear regression in R: autocorrelated residuals
I'm trying to estimate a multiple linear regression in R with an equation like this:
regr <- lm(rate ~ constant + askings + questions + 0)
askings and ...
5
votes
1answer
366 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 ...
5
votes
1answer
844 views
Two sample t-test for data (maybe time series) with autocorrelation?
I am new to statistics, so pardon any mistakes in my question.
I have two time series $X_i$ and $Y_i$. Assuming that they're stationary AR(1) processes with possibly different means, how do I test ...
5
votes
1answer
206 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 ...
5
votes
2answers
126 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 ...
4
votes
4answers
386 views
Analyze and generate “clumpy” distributions?
Are there standard ways of analyzing and generating "clumpy" distributions?
analyze: how clumpy is a given point cloud (in 1d, 2d, nd),
what are its clumpy coefficients?
generate or synthesize a ...
4
votes
1answer
113 views
Algorithm to produce autocorrelated uniformly distributed number
I would like to produce a time-series of autocorrelated probabilities (with a predefined mean level of autocorrelation).
I've spotted this and this which I believe should give me what I'm looking ...
4
votes
3answers
6k views
Autocorrelation and heteroskedasticity in panel data
In the research, both autocorrelation and heteroskedasticity are detected in panel data analysis. I can solve them separately in stata with command "xtregar" and "robust", respectly. However, I cannot ...
4
votes
2answers
101 views
ARIMA — Residual autocorrelation is non-significant upto lag 6 and significant beyond lag 6
I tried to fit an AR(1) model and was examining the estimates of the model. I had a question on the output (ran in SAS - Proc ARIMA):
The residual auto-correlation up to lag 6 was non-significant (in ...
4
votes
1answer
410 views
What is the power of the Ljung-Box Test for auto-correlation?
How large sample size should be for Ljung-Box statistic to achieve a power $\ge 0.5$ when number of lags tested is 1? How does the power fall ( assuming an AR(1) process), with increasing number of ...
4
votes
1answer
213 views
Smoothness of a surface
I am currently working on a model which takes two parameters and produces a measurement statistic. Think of it as Z = f(X,Y).
Z is a matrix of my statistics and I am creating a surface plot of it in ...
4
votes
1answer
184 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 ...
4
votes
3answers
328 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 ...
4
votes
1answer
254 views
In spatial regression, what is a spherical autocorrelation structure?
I have a large gridded dataset for the globe (i.e a spherical, wraparound surface) that I'm applying spatial regression to (using a CAR model). I've been using the default autocorrelation function, ...
4
votes
3answers
2k views
How can the IID assumption be checked in a given dataset?
1- How can I check if a set of data can be assumed as IID data?
I'm not so familiar with statistics, but I guess I should look at the first lag of autocorrelation for independent distribution. Have no ...
4
votes
2answers
504 views
Outlier detection for generic time series
In this case, "generic" being the entire gauntlet of macroeconomic time-series that private and government statistical offices put out.
Some background - I recently started working at a data provider ...
4
votes
1answer
2k views
What to read from the autocorrelation function of a time series?
Given a time series, one can estimate the autocorrelation-function and plot it, for example as seen below:
What is it then possible to read about the time series, from this ...
4
votes
0answers
35 views
Inducing autocorrelation by fitting the wrong ARMA?
I am trying to fit an ARMA(p,q) model to the mean equation of my return series. The problem is, that the acf and pacf are pretty not usable, i.e. it is hard to find a good model to take account of the ...
4
votes
0answers
71 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 ...
4
votes
0answers
349 views
What is the best way to compare fluctuations of two signals?
I have some data acquired by an acoustic sensor with 1 Hz sampling rate. Due to some inevitable issues, I have some noise in my signal, saying 10% pollution.
I'm looking for a reliable method for ...
3
votes
3answers
712 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
318 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 ...
3
votes
1answer
629 views
PACF manual calculation
I am trying to replicate the calculation that SAS and SPSS do for the partial autocorrelation function (PACF). In SAS it is produced through Proc Arima. The PACF values are the coefficients of an ...
3
votes
3answers
573 views
How to deal with gaps/NaNs in time series data when using Matlab for autocorrelation and neural networks?
I have a time series of measurements (heights-one dimensional series). In the observation period, the measurement process went down for some time points. So the resulting data is a vector with NaNs ...
3
votes
2answers
74 views
Confidence bands in case of fitting ARIMA in R?
I want to look at the acf and pacf of my data, to identify the model for my mean equation, so I want to fit an ARMA for my mean equation and later on model the conditional variance by a ARCH/GARCH (I ...
