Comments (1)
weikang9009
commented on June 17, 2024
Hi @Daydreamerla, thank you for your interest in using spatial Markov methods. Related to your questions:
- us48.gal is a spatial weight file. You can use
libpysalto generate a spatial weight object that can be used in your analysis. You may read the GDS book to learn more about spatial weights and how to construct different types of spatial weights using PySAL. - You will need to organize panel data in the form of a n by t numpy array and pass it to
Spatial_Markovas the first argument.
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Related Issues (20)
- development guidelines link in README.md HOT 1
- Release version 2.2.2 for bug fix
- spatial_dynamics.interaction migration? HOT 5
- Links broken with https://github.com/pysal/giddy/tutorial
- Binder for examples is missing dependencies HOT 1
- output for classic Markov needs slight rewording HOT 2
- Ability to use a generated spatial markov chain to predict the next n states HOT 6
- CI needs redesign HOT 3
- change master to main HOT 3
- Spatial_Markov gives its own set of 'k' classes even though explicitly mentioned as paramter value HOT 4
- add gha workflow for publishing docs HOT 10
- Prepare for a new realase before the Jan meta-package release
- v2.3.4 release HOT 5
- Update bleeding edge `libpysal` in dev envs
- Related to "giddy.markov.Homogeneity_Results" command HOT 2
- ValueError: setting an array element with a sequence
- update supported for Python version HOT 3
- how use my own data HOT 1
- notebook links are returning 404 HOT 2
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