… [28], which laid the foundation for the use of spatial regression models. … a spatial regression
model instead of the traditional OLS regression model to analyze the impact of urban density …

… The study of urban population and crime almost 190 years old and it based on a noble first …
They found urban population composition is among size of city, population urban density and …

… regression analysis were not collinear. IR was the ratio of impermeable non-building canopies
such as urban roads, so the quantitative analyses of building density … regression analysis, …

… The measure of density is floor space per … Regression of log density on distance from the
city centre provides a good fit, but with uniformly lower R2's than the regression of log of density …

… The method is as follows: Co-Plot is based on the integration of mapping concepts with a
variant of regression analysis. It starts with a data matrix Y n×p of n rows and p columns; the …

… regression analysis method called “least absolute shrinkage and selection operator” (LASSO)
[41] were also used. CFS can be considered as a preprocessing step and is independent …

… One strategy to improve the fit of density regression analyses is to estimate separate density
functions for different radial sectors of an urban area. Kramer [43] followed this strategy in …

… The driving factors in this study were divided in two types: density and proximity. The driving
… regression is used for urban growth modeling in a tsunami-prone city. A logistic regression …

… have argued that a high-density compact urban form does not significantly improve air quality
and may even lead to more serious air pollution. Using a panel data analysis of 17 cities in …

… regression framework for modeling urban population density. In this framework, urban
population density is … upon linear regression analysis coupled with a normal probability model: …