this paper is a part of study about the impact of the microclimate on the space use and the user’s behaviours. the purpose of our study is to get an in-depth understanding of how people use out door public spaces in different climatic conditions, how their behaviour and perception of the space change with the climatic variations. we have employed a multi-method approach which combines a “qualit...

In this paper, a new discriminant analysis for feature extraction is derived from the perspective of least squares regression. To obtain great discriminative power between classes, all the data points in each class are expected to be regressed to a single vector, and the basic task is to find a transformation matrix such that the squared regression error is minimized. To this end, two least squ...

Necessary and su cient conditions for the equality of ordinary least squares and generalized least squares estimators in the linear regression model with rst order spatial error processes are given

This article introduces the use of regression models based on the Poisson distribution as a tool for resolving common problems in analyzing aggregate crime rates. When the population size of an aggregate unit is small relative to the offense rate, crime rates must be computed from a small number of offenses. Such data are ill-suited to least-squares analysis. Poisson-based regression models of ...

This paper aims to analysis the behavior of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Currentvoltage curves are particularly analyzed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: l...

One of the most commonly used methods for the analysis of experimental data in the biochemical literature is nonlinear least squares (regression). This group of methods are also commonly misused. The purpose of this article is to review the assumptions inherent in the use of least-squares techniques and how these assumptions govern the ways that least-squares techniques can and should be used. ...