Durbin and Watson have suggested a test to detect the presence ofautocorrelationwhich applies to small samples. However, the test is appropriate only for the first-order autoregressive scheme ($u_t = \rho u_{t-1} + \varepsilon_t$). Step by Step procedure for the Durbin-Watson Test Step...
big-data statistical-analysis autocorrelation remote-sensing-in-r Updated Sep 15, 2023 R olivercliff / assessing-linear-dependence Star 17 Code Issues Pull requests A package to compute and test the significance of linear dependence between multiple autocorrelated time series. autocorrelation mutual...
The precise calculation used to conduct this test can be found here. Once you have successfully plugged your numbers into the Durbin-Watson test, it reports a statistic on a value of 0 to 4. If the value returned is 2, there is no autocorrelation in your time series to speak of. If ...
For each SWM, the input field is tested for statistically significant spatial autocorrelation using a permutation test of Moran's I. If the spatial autocorrelation is not statistically significant (the p-value is greater than 0.05) for all SWMs, the tool will fail and the input field...
Fill in all parameters and filenames in the Input Parameters Section of STREAM_config.pyRun "python STREAM_config.py" from the command line.Formatting input data for STREAMpcp_file should be a netcdf file with coordinates (time,lat,lon). The user defines the variable name, pvar, and can...
), poker test (a special instance of the chi-squared test), runs test (counts the frequency of runs of various lengths), longruns test (checks whether there exists any run of length 34 or greater in 20 000 bits of the sequence)—both from BSI and NIST, and the autocorrelation test. ...