Autocorrelation       Article     History   Tree Map
  Encyclopedia of Keywords > Information > Science > Mathematics > Statistics > Autocorrelation   Michael Charnine

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  1. Autocorrelation is a mathematical tool used frequently in signal processing for analysing functions or series of values, such as time domain signals. (Web site)
  2. The autocorrelation is a Hermitian operator since .
  3. The autocorrelation is a function (of j) while the autocovariance is a number. (Web site)
  4. Autocorrelation is a method for identifying time-related patterns within a data set. (Web site)
  5. Autocorrelation is an interesting concept and is very useful in attempting to observe patterns in time-series data. (Web site)

Spatial Autocorrelation

  1. The spatial autocorrelation was calculated using Moran's I with contiguity as well as distance weighting. (Web site)
  2. In geographic applications there is usually positive spatial autocorrelation.
  3. In order to incorporate distance as a measure of spatial autocorrelation we use contiguity as well as distance to define the weighting function. (Web site)


  1. If the ordinary Durbin-Watson test indicates no first-order autocorrelation, you can use the second-order test to check for second-order autocorrelation.
  2. In this case, the first-order Durbin-Watson test is highly significant, with p < .0001 for the hypothesis of no first-order autocorrelation.
  3. Small values of the Durbin-Watson statistic indicate the presence of autocorrelation. (Web site)


  1. The autocorrelogram indicates that we removed too much of the lag 1 and lag 12 components, as they have now negative autocorrelation coefficients.
  2. Responses to autocorrelation include differencing of the data and the use of lag structures in estimation.


  1. Since autocorrelation is a specific type of cross-correlation, it maintains all the properties of cross-correlation. (Web site)
  2. CORR, a numeric variable containing the autocorrelation or cross-correlation function values.
  3. These methods include autocorrelation and cross-correlation of time series. (Web site)

Autocorrelation Function

  1. As the lag increases, the autocorrelation function of short-range dependent processes decays quickly. (Web site)
  2. When a process is under minimum variance control, the autocorrelation function is zero for all lags greater than the process deadtime.
  3. Structure in the autocorrelation function may provide clues about what is causing the clusters of packet drops from an individual mailbox queue. (Web site)
  4. The only difference then is whether other methods like Fourier analysis might give you more information than the autocorrelation function.


  1. The autocorrelation of a periodic function is, itself, periodic with the very same period. (Web site)
  2. Negative autocorrelation means standard errors are too large.
  3. Scaling The type of scaling for the autocorrelation: None, Biased, Unbiased, or Unity at zero-lag. (Web site)
  4. As such, interpolation was performed only where this was true for both autocorrelation statistics.
  5. Strong autocorrelation in the squared returns is also a symptom of changing unconditional or conditional 4 variance.


  1. When normalised by dividing by the variance -- 2 then the autocovariance becomes the autocorrelation R( k).
  2. It is common practice in many disciplines to drop the normalisation by -- 2 and use the term autocorrelation interchangeably with autocovariance. (Web site)


  1. Autocorrelation: Autocorrelation is the serial correlation of equally spaced time series between its members one or more lags apart. (Web site)
  2. In order to confirm this trend we are going to analyse the autocorrelation function of the series.
  3. Computes the sample autocorrelation function of a stationary time series.
  4. In addition, autocorrelation plots are used in the model identification stage for Box-Jenkins autoregressive, moving average time series models. (Web site)


  1. AutoCorrelation.NonPosVariancesException - exception com.imsl.stat.
  2. AutoCorrelation(double[], int) - Constructor for class com.imsl.stat.


  1. In a sample, the kth autocorrelation is the OLS estimate that results from the regression of the data on the kth lags of the data. (Web site)
  2. There are relatively well known adjustments for the variance estimates in OLS that are robust to general forms of heteroskedasticity or autocorrelation. (Web site)


  1. Alternatively, signals that last forever can be treated by a short-time autocorrelation function analysis, using finite time integrals. (Web site)
  2. Formally, the discrete autocorrelation R at lag j for signal xn is Figure--3(3)(Wikipedia 2006) where m is the average value (expected value) of xn. (Web site)


  1. This test is based on the autocorrelation plot and is commonly used in the context of ARIMA modeling. (Web site)
  2. Autocorrelation plots are also used in the model identification stage for fitting ARIMA models. (Web site)


  1. Spatial autocorrelation can be analyzed using correlograms, covariance functions and variograms (=semivariograms).
  2. Kriging models use a semivariogram to depict the spatial autocorrelation between measured sample points. (Web site)
  3. Spatial autocorrelation statistics are used to describe the relationships between data observed at different geographic locations. (Web site)
  4. The table below summarizes the results of spatial autocorrelation tests, variogram fitting, and kriging cross validation.
  5. Both spatial error autocorrelation as well as heteroskedasticity are therefore incorporated in the SAR model.


  1. The Autocorrelation block does not accept a sample-based full-dimension matrix input. (Web site)
  2. The block computes the autocorrelation along each column of a frame-based input, and computes along the vector dimension of a sample-based vector input. (Web site)
  3. The following diagram shows the data types used within the Autocorrelation block for fixed-point signals.


  1. Maximum non-negative lag (less than input length) Specify the maximum positive lag, l, for the autocorrelation.
  2. Compute all non-negative lags Select to compute the autocorrelation over all nonnegative lags in the range [ 0, length(input)-1].


  1. In statistics, the autocorrelation function (ACF) of a random process describes the correlation between the process at different points in time. (Web site)
  2. However, correlation is limited to autocorrelation in a single variable. (Web site)
  3. This patent does not employ autocorrelation or cross correlation and does not use a quality control chart. (Web site)


  1. The autocorrelation plot is an excellent way of checking for such randomness. (Web site)
  2. The plot consists of: Vertical axis = subsample autocorrelation; Horizontal axis = subsample index. (Web site)

Cross Covariance

  1. The autocorrelation function and cross correlation function are normalized versions of the autocovariance and cross covariance functions.
  2. However, the user also cannot inspect any time series functions such as the autocorrelation function, cross covariance function, power spectrum, etc.


  1. The continuous autocorrelation function reaches its peak at the origin, where it takes a real value, i.e. (Web site)
  2. The Autocorrelation block accepts both real and complex floating-point inputs.


  1. Spatial autocorrelation statistics can be calculated for polygon as well as point coverages. (Web site)
  2. Arc Attribute Tables and Polygon Attribute Tables), and these tables are very useful for calculating various autocorrelation statistics. (Web site)


  1. Different definitions of autocorrelation are in use depending on the field of study which is being considered and not all of them are equivalent.
  2. I have tried to reconcile the differing definitions of autocorrelation in different disciplines. (Web site)


  1. An appropriate test for residual autocorrelation is provided by the LM test in § 18.4.3 below.
  2. The LM tests for autocorrelation, heteroscedasticity and functional form require an auxiliary regression involving the original regressors x it.


  1. This output has the same form as the autocorrelation check for white noise that the IDENTIFY statement prints for the response series.
  2. Inaddition, PcGive prints the partial autocorrelation function (PACF) (see the OxMetrics book).


  1. An indication of ARCH is that the residuals will be uncorrelated but the squared residuals will show autocorrelation. (Web site)
  2. It is usually used to test for autocorrelation in regression residuals rather than for spurious correlation. (Web site)
  3. However, the sample autocorrelation function of the squared residuals tells a different story. (Web site)
  4. Nonetheless, the GARCH model presented is designed to account for any heteroskedasticity and serial autocorrelation within the residuals.


  1. At zero time the autocorrelation function is positive since it is the means square value of the flux at equilibrium.
  2. Independent observations (absence of autocorrelation) leading to uncorrelated error terms. (Web site)
  3. We model the system as an autoregressive one, and our proposal is based on the calculation of the poles of the autocorrelation function. (Web site)
  4. It makes use of information extra to that usually used in 'traditional' signal processing measures such as the power spectrum and autocorrelation function.


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