The autocorrelation tag has no wiki summary.
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3answers
572 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 ...
0
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1answer
114 views
What's statistic should I use to determine if Time Series A (economic) is a leading indicator of Time Series B (Sales)
I'm trying to utilize economic and industry data to forecast sales of industrial companies. I have numerous economic and industry indices and as a first step I would like to indentify those indices ...
6
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1answer
166 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 ...
3
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1answer
790 views
Autocorrelation in panel data
I have a random effects panel data model with 4 variables, 10 years of data and 946 observations describing different financial values for different companies. The panel is balanced. The model looks ...
6
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0answers
601 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
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2answers
370 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 ...
4
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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, ...
3
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1answer
627 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 ...
1
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1answer
191 views
Are HAC estimators used for estimation of regression coefficients?
The references I can find on HAC procedures (like Newey-West) in regression focus on the standard error of the estimated regression coefficients and hypothesis testing involving the same. I cannot ...
4
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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 ...
3
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2answers
5k views
Interpreting coefficients from a VECM (Vector Error Correction Model)
I would like to ask a question about error correction terms from VECM if I may. I am currently working on a lot of time-series data and one of the questions I would like to address is whether there is ...
3
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0answers
217 views
How to estimate measurement error on spatially autocorrelated gridded data when aggregating grid cells
I would like to estimate the measurement error when aggregating (via arithmetic mean) gridded spatial data. The goal is to come up with the mean elevation (or some other spatially continuous ...
2
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1answer
309 views
Bias of autocorrelation function in finite sample for ARMA processes
I remember reading that, when estimating the autocorrelation function of a univariate ARMA time series using finite samples, the estimate is biased and specifically the lag-1 ACF is negatively biased ...
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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 ...
3
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3answers
188 views
Literature on generating “similar” synthetic time series from observed time series
The motivation for this question is from Finance. I have some market data (daily time series) for the price of some securities and I would like to generate synthetic versions of these which are ...
7
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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:
...
2
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1answer
244 views
When was the autocorrelation function invented? And what was the motivation for it?
I'm just very curious about the discovery process behind the autocorrelation function.
When was it invented?
Was it independently invented multiple times, for example?
What was the motivation for ...
4
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2answers
502 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 ...
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2answers
835 views
Forecasting stock prices time series based on independent factors using ARIMA model
I am trying to forecast time series of stock for a particular case in which closing value of the stock depends on independent factors which is in which infact another time series.
Situation is like I ...
0
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1answer
244 views
Time series autocorrelation
The definition for the $k$-th lag auto correlation is $Cov(y_t,y_{t-k})/Var(y_t)$.
My question is why should not it be $Cov(y_t,y_{t-k})/[Var(y_t)\cdot Var(y_{t-k})]^{0.5}$.
In another words, what ...
1
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1answer
309 views
Autocorrelation vs correlation calculation
I have set $x = {1,2,3,4,5}$ and set $y = {2,3,4,5,6}$. Lets say the correlation of $x$ and $y$ is $0.7$. If I then have set $z = {1,2,3,4,5,2,3,4,5,6}$, and I do autocorrelation using lag $=$ $5$, ...
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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 ...
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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 ...
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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 ...
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0answers
559 views
Panel Data: In a fixed effects model, does auto-correlation introduce bias?
Given a panel of countries over time, a fixed effects estimator makes sense to control for country-specific effects. My intuition tells me that if the dependent variable is correlated with lags of the ...
2
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3answers
431 views
How to exploit periodicity to reduce noise of a signal?
100 periods have been collected from a 3 dimensional periodic signal. The wavelength slightly varies. The noise of the wavelength follows Gaussian distribution with zero mean. A good estimate of the ...
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1answer
2k views
How can I calculate the autocorrelation of a signal in Mathematica environment?
I tried CorrelationFunction[Transpose[{data,data}]][[All,1,2]] but it doesn't work! I mean the results are identical with those if I run ...
6
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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 ...
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2answers
366 views
Methods for evaluating partial autocorrelation for identification of ARIMA models
I am trying to programmatically identify an ARIMA model for a series of data and forecast values.
Currently the problem i am facing is to find a way to evaluate partial autocorrelation. I have been ...
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0answers
235 views
Estimating noise correlation in augmented state vector Kalman filter
How do I estimate the noise correlation matrix (psi function) in the augmented state approach of Kalman filter?
Can I do something like this:
$$\text{noise}_2 = \psi \cdot ...
6
votes
1answer
733 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 ...
4
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1answer
408 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 ...
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0answers
1k views
Calculate Cross Correlation of two matrices of the 'Values Vs. Time' representation
I have 2 acceleration vectors, each represented by a matrix with its first column corresponding to the magnitude of acceleration and second column corresponding to the time (in ms) They both represent ...
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3answers
956 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 ...
5
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1answer
842 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 ...
9
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1answer
373 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 ...
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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 ...
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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...
6
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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 ...
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1answer
291 views
Wavelet auto correlation
I have a time serie that I want to analyse through a wavelet decomposition.
I am using the R package WaveThres.
I am interested in the wavelet autocorrelation, but I struggle to understand what ...
7
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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 ...
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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 ...
10
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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 ...
4
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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
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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 ...
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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 ...
