scholarly journals Intermittent reservoir daily-inflow prediction using lumped and distributed data multi-linear regression models

2011 ◽  
Vol 120 (6) ◽  
pp. 1067-1084 ◽  
Author(s):  
R B MAGAR ◽  
V JOTHIPRAKASH
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Distributed Data ◽  
Linear Regression Models ◽  
Multi Linear Regression ◽  
Inflow Prediction

scholarly journals Multi-linear Regression Models to Predict the Annual Energy Consumption of an Office Building with Different Shapes

2015 ◽  
Vol 118 ◽  
pp. 622-629 ◽  
Author(s):  
Mohammad Mottahedi ◽  
Atefeh Mohammadpour ◽  
Shideh Shams Amiri ◽  
David Riley ◽  
Somayeh Asadi
Keyword(s):  
Energy Consumption ◽  
Linear Regression ◽  
Regression Models ◽  
Office Building ◽  
Linear Regression Models ◽  
Multi Linear Regression ◽  
Different Shapes

ADDING REGRESSORS TO OBTAIN EFFICIENCY

2009 ◽  
Vol 25 (1) ◽  
pp. 298-301 ◽  
Author(s):  
Sung Jae Jun ◽  
Joris Pinkse
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Asymptotic Efficiency ◽  
Asymptotic Variance ◽  
Generalized Least Squares ◽  
Conditional Heteroskedasticity ◽  
Distributed Data ◽  
Linear Regression Models ◽  
Generalized Least Squares Estimator ◽  
Standard Linear

It is well known that in standard linear regression models with independent and identically distributed data and homoskedasticity, adding “irrelevant regressors” hurts (asymptotic) efficiency unless such irrelevant regressors are orthogonal to the remaining regressors. But we have found that under (conditional) heteroskedasticity “irrelevant regressors” can always be found such that one can achieve the asymptotic variance of the generalized least squares estimator by adding the “irrelevant regressors” to the model.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Sign in / Sign up

Export Citation Format

Share Document