Hourly cooling load forecasting using time-indexed ARX models with two-stage weighted least squares regression

2014 ◽  
Vol 80 ◽  
pp. 46-53 ◽  
Author(s):  
Yin Guo ◽  
Ehsan Nazarian ◽  
Jeonghan Ko ◽  
Kamlakar Rajurkar
2020 ◽  
Vol 50 (4) ◽  
pp. 1252-1259 ◽  
Author(s):  
Grant S. Galloway ◽  
Victoria M. Catterson ◽  
Craig Love ◽  
Andrew Robb ◽  
Thomas Fay

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Janet Myhre ◽  
Daniel R. Jeske ◽  
Michael Rennie ◽  
Yingtao Bi

A heteroscedastic linear regression model is developed from plausible assumptions that describe the time evolution of performance metrics for equipment. The inherited motivation for the related weighted least squares analysis of the model is an essential and attractive selling point to engineers with interest in equipment surveillance methodologies. A simple test for the significance of the heteroscedasticity suggested by a data set is derived and a simulation study is used to evaluate the power of the test and compare it with several other applicable tests that were designed under different contexts. Tolerance intervals within the context of the model are derived, thus generalizing well-known tolerance intervals for ordinary least squares regression. Use of the model and its associated analyses is illustrated with an aerospace application where hundreds of electronic components are continuously monitored by an automated system that flags components that are suspected of unusual degradation patterns.


2011 ◽  
Vol 130-134 ◽  
pp. 730-733
Author(s):  
Narong Phothi ◽  
Somchai Prakancharoen

This research proposed a comparison of accuracy based on data imputation between unconstrained structural equation modeling (Uncon-SEM) and weighted least squares (WLS) regression. This model is developed by University of California, Irvine (UCI) and measured using the mean magnitude of relative error (MMRE). Experimental data set is created using the waveform generator that contained 21 indicators (1,200 samples) and divided into two groups (1,000 for training and 200 for testing groups). In fact, training group was analyzed by three main factors (F1, F2, and F3) for creating the models. The result of the experiment show MMRE of Uncon-SEM method based on the testing group is 34.29% (accuracy is 65.71%). In contrast, WLS method produces MMRE for testing group is 55.54% (accuracy is 44.46%). So, Uncon-SEM is high accuracy and MMRE than WLS method that is 21.25%.


2019 ◽  
Vol 34 (4) ◽  
pp. 374-392 ◽  
Author(s):  
Muhammad Usman ◽  
Muhammad Umar Farooq ◽  
Junrui Zhang ◽  
Muhammad Abdul Majid Makki ◽  
Muhammad Kaleem Khan

Purpose This paper aims to investigate the question concerning whether gender diversity in the boardroom matters to lenders or not? Design/methodology/approach To answer this question, the authors use the data from 2009 to 2015 of all A-share listed companies on the Shanghai and Shenzhen stock exchanges. The authors use ordinary least squares regression and firm fixed effect regression to draw our inferences. To check and control the issue of endogeneity the authors use one-year lagged gender diversity regression, two-stage least squares regression, propensity score matching method and Heckman two-stage regression. Findings The results suggest that the presence of female directors on the board reduces managerial opportunistic behavior and information asymmetry and, consequently, creditors’ perceptions about the probability of loan default and the cost of debt. The authors find that lenders charge 4 per cent less from borrowers that have at least one female board member than they do from borrowers with no female board members. The authors also find that the board structure (i.e. gender diversity) of government-owned firms also matters to lenders, as government-owned firms that have gender-diverse boards have a lower cost of debt (i.e. 5 per cent lower interest rate). Practical Implications The findings have implications for individual borrowers and for regulators. For example, borrowers can get debt financing at lower rates by altering their boards’ composition (i.e. through gender diversity). From the regulatory perspective, the results support recent legislative initiatives around the world regarding female directors’ representation on boards. Originality Value This paper makes several contributions. First, beyond the recent studies on boardroom gender, the authors investigate the relationship between gender diversity in the boardroom and the cost of debt. Second, the authors extend the literature on the association between government ownership and cost of debt by first time providing evidence that the board composition (e.g. gender diversity) of government-owned firms also matters to the lenders. The other contributions are discussed in the introduction section.


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