| contributor author | Ali Pirdavani | |
| contributor author | Tom Bellemans | |
| contributor author | Tom Brijs | |
| contributor author | Geert Wets | |
| date accessioned | 2017-05-08T22:10:34Z | |
| date available | 2017-05-08T22:10:34Z | |
| date copyright | August 2014 | |
| date issued | 2014 | |
| identifier other | 37190643.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/72868 | |
| description abstract | Generalized linear models (GLMs) are the most widely used models utilized in crash prediction studies. These models illustrate the relationships between the dependent and explanatory variables by estimating fixed global estimates. Since crash occurrences are often spatially heterogeneous and are affected by many spatial variables, the existence of spatial correlation in the data is examined by means of calculating Moran’s | |
| publisher | American Society of Civil Engineers | |
| title | Application of Geographically Weighted Regression Technique in Spatial Analysis of Fatal and Injury Crashes | |
| type | Journal Paper | |
| journal volume | 140 | |
| journal issue | 8 | |
| journal title | Journal of Transportation Engineering, Part A: Systems | |
| identifier doi | 10.1061/(ASCE)TE.1943-5436.0000680 | |
| tree | Journal of Transportation Engineering, Part A: Systems:;2014:;Volume ( 140 ):;issue: 008 | |
| contenttype | Fulltext | |
