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This example pipeline requires the addition of several new blocks. Here is a preliminary list - please let me know if you think anything is missing or should be changed:
- MitchCal for self-calibratio…
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```
from Aug 18, 2012
Currently, the global Moran's I statistic for spatial autocorrelation we have
in GeoDa is linear. Luc has been interested in adding nonlinear tests and
displays (e.g. copula, …
-
```
from Aug 18, 2012
Currently, the global Moran's I statistic for spatial autocorrelation we have
in GeoDa is linear. Luc has been interested in adding nonlinear tests and
displays (e.g. copula, …
-
```
Measures of spatial autocorrelation compute permutation-based pseudo p-values.
While comparing Getis and Ord local G stats across PySAL and GeoDa, two issues
have appeared.
1. PySAL computes st…
-
```
from Aug 18, 2012
Currently, the global Moran's I statistic for spatial autocorrelation we have
in GeoDa is linear. Luc has been interested in adding nonlinear tests and
displays (e.g. copula, …
-
```
Measures of spatial autocorrelation compute permutation-based pseudo p-values.
While comparing Getis and Ord local G stats across PySAL and GeoDa, two issues
have appeared.
1. PySAL computes st…
-
This week I made more progress with the automated GWPD data import process. At this point, the only thing I need to do with it is finish implementing the building name to lat/lon lookup, and then we w…
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```
The LM statistics for residual spatial autocorrelation reported are
different from those with GeoDaSpace for k nearest neighbor weights.
This is the case for both 1.6 and 1.7. This is NOT the case…
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As we discussed on Friday, we now have the GWPD data import working, and we can now run the spatial autocorrelation algorithm against this data. Now, we must get the rest of the data imported and cont…