Space-Time Analysis of Regional Systems (STARS)

Space-Time Analysis of Regional Systems (STARS) is an open-source package designed for the dynamic exploratory analysis of data measured for areal units at multiple modules

Human Statics
  1893

Contributor(s)

Initial contribute: 2018-01-02

Authorship

Affiliation:  
UNIVERSITY OF CALIFORNIA, RIVERSIDE
Email:  
sjsrey@gmail.com
Homepage:  
View
Affiliation:  
New Jersey Institute of Technology | NJIT · Department of Information Systems
Email:  
xinyue.ye@njit.edu
Homepage:  
View
Is authorship not correct? Feed back

Classification(s)

Application-focused categoriesHuman-perspectiveSocial activities

Model Description

English {{currentDetailLanguage}} English

Basic Information

Space-Time Analysis of Regional Systems (STARS) is an open-source package designed for the dynamic exploratory analysis of data measured for areal units at multiple modules: Anselin (1995) points in time. STARS consists of four core analytical exploratory spatial data analysis; Anselin (2003) inequality measures; Carlino and Mills (1993) mobility metrics; and Christakos, Bogaert , and Serre (2001)spatial Markov. Developed using the Python object-oriented scripting language, STARS lends itself to three main modes of use. Within the context of a command line interface (CLI), STARS can be treated as a package which can be called from within customized scripts for batch-oriented analyses and simulation. Alternatively ,a graphical user most of the series of (GUI) integrates analytical modules interface with a dynamic graphical views containing brushing and linking functionality to support the interactive exploration of the spatial, temporal, and distributional dimensions of socioeconomic and physical processes .Finally ,the GUI and CLI modes can be combined for use from the Python shell to facilitate interactive programming and access to the many libraries contained within Python.

 

How to Cite

Sergio J Rey, Xinyue Ye (2018). Space-Time Analysis of Regional Systems (STARS), Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/6e512338-5c96-45ee-99b9-31d7df3fb311
Copy

QR Code

Contributor

Initial contribute: 2018-01-02

Co-contributor(s)

Authorship

Affiliation:  
UNIVERSITY OF CALIFORNIA, RIVERSIDE
Email:  
sjsrey@gmail.com
Homepage:  
View
Affiliation:  
New Jersey Institute of Technology | NJIT · Department of Information Systems
Email:  
xinyue.ye@njit.edu
Homepage:  
View
Is authorship not correct? Feedback

QR Code

×

{{curRelation.overview}}
{{curRelation.author.join('; ')}}
{{curRelation.journal}}









Related Items

You can link resource from repository to this model item, or you can create a new {{typeName.toLowerCase()}}.

Drop the file here, orclick to upload.
Select From My Space
+ add

These authorship information will be submitted to the contributor to review.

Cancel Submit
Cancel Submit
Localizations + Add
{{ item.label }} {{ item.value }}
Model Name :
Cancel Submit Cancel Submit
Name:
Version:
Model Type:
Model Domain:
Scale:
Purpose:
Principles:
Incorporated models:

Model part of

larger framework

Process:
Information:
Initialization:
Hardware Requirements:
Software Requirements:
Inputs:
Outputs:
Cancel Submit
Title Author Date Journal Volume(Issue) Pages Links Doi Operation
Cancel Submit
Add Cancel

{{articleUploading.title}}

Authors:  {{articleUploading.authors[0]}}, {{articleUploading.authors[1]}}, {{articleUploading.authors[2]}}, et al.

Journal:   {{articleUploading.journal}}

Date:   {{articleUploading.date}}

Page range:   {{articleUploading.pageRange}}

Link:   {{articleUploading.link}}

DOI:   {{articleUploading.doi}}

Yes, this is it Cancel

The article {{articleUploading.title}} has been uploaded yet.

OK
Cancel Confirm