On Linear Algebra, the Least Square Method, and the Search for Linear Relations by Regression Analysis in Quantum Chemistry and Other Sciences

1992 ◽  
pp. 83-126 ◽  
Author(s):  
Per-Olov Löwdin
Keyword(s):  
Regression Analysis ◽  
Quantum Chemistry ◽  
Linear Algebra ◽  
Least Square Method ◽  
Least Square ◽  
Linear Relations

scholarly journals PENGARUH KEMAMPUAN KEUANGAN DAERAH TERHADAP PERTUMBUHAN EKONOMI DI WILAYAH SUMATERA SELATAN PERIODE 2005-2014

MOTIVASI ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 207
Author(s):  
Juairiah Juairiah
Keyword(s):  
Economic Growth ◽  
Regression Analysis ◽  
Panel Data ◽  
Design Methodology ◽  
Least Square Method ◽  
Least Square ◽  
Financial Capacity ◽  
Effect Estimation ◽  
Analysis Models ◽  
Estimation Models

Purpose – The study aims to determine how the influence of financial capacity of region on economic growth in Southern Sumatran Region in period 2005 to 2014.Design/methodology - The analysis was performed by multiple regression analysis models by a Pooled Least Square method and the fixed effect estimation models. The data used is panel data of five provinces in Southern Sumatra.Findings – The analysis showed that the financial capacity in Southern Sumatra region is significantly affecting the economic growth.

scholarly journals Determinant Analysis of Bilateral Trade Between Indonesia and Yemen During the Period 1990-2015: A Gravity Model Approach

2017 ◽  
Vol 1 (2) ◽  
pp. 37
Author(s):  
Sulthon Sjahril Sabaruddin
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Gravity Model ◽  
Bilateral Trade ◽  
Least Square Method ◽  
Least Square ◽  
Political Uncertainty ◽  
Independent Variables ◽  
Trade Model

This study examines the factors that influence the performance of bilateral trade between Indonesia and Yemen. In conducting the study, the authors use the conventional bilateral trade model is modified gravity model of international trade approach by using multiple regression analysis with Ordinary Least Square method. The analysis finds that the three independent variables that significantly affect the value of bilateral trade between Indonesia –Yemen is the GDP of Yemen, political uncertainty and security in Indonesia, as well as the presence of Indonesian Representative in the Republic of Yemen. While other independent variables namely Indonesia's GDP and political uncertainty and security in Yemen, based on the conclusions statistically, the two independent variables do not yet have enough evidence to say that the GDP of Indonesia and political uncertainty and security in Yemen significantly affect bilateral trade between Indonesia-Yemen. This trade gravity model previously passed testing assumptions multiple regression analysis with hypothesis testing and the accuracy of the model.

scholarly journals Comparison of M Estimation, S Estimation, with MM Estimation to Get the Best Estimation of Robust Regression in Criminal Cases in Indonesia

2022 ◽  
Vol 18 (2) ◽  
pp. 251-260
Author(s):  
Malecita Nur Atala Singgih ◽  
Achmad Fauzan
Keyword(s):  
Regression Analysis ◽  
Robust Regression ◽  
Estimation Method ◽  
Least Square Method ◽  
Influential Factors ◽  
Least Square ◽  
Method Of Moment ◽  
Best Estimate ◽  
M Estimation ◽  
Mm Estimation

Crime incidents that occurred in Indonesia in 2019 based on Survey Based Data on criminal data sourced from the National Socio-Economic Survey and Village Potential Data Collection produced by the Central Statistics Agency recorded 269,324 cases. The high crime rate is caused by several factors, including poverty and population density. Determination of the most influential factors in criminal acts in Indonesia can be done with Regression Analysis. One method of Regression Analysis that is very commonly used is the Least Square Method. However, Regression Analysis can be used if the assumption test is met. If outliers are found, then the assumption test is not completed. The outlier problem can be overcome by using a robust estimation method. This study aims to determine the best estimation method between Maximum Likelihood Type (M) estimation, Scale (S) estimation, and Method of Moment (MM) estimation on Robust Regression. The best estimate of Robust Regression is the smallest Residual Standard Error (RSE) value and the largest Adjusted R-square. The analysis of case studies of criminal acts in Indonesia in 2019 showed that the best estimate was the S estimate with an RSE value of 4226 and an Adjusted R-square of 0.98  

scholarly journals A Driving Behaviour Model of Electrical Wheelchair Users

2016 ◽  
Vol 2016 ◽  
pp. 1-20 ◽  
Author(s):  
S. O. Onyango ◽  
Y. Hamam ◽  
K. Djouani ◽  
B. Daachi ◽  
N. Steyn
Keyword(s):  
Regression Analysis ◽  
Control System ◽  
Virtual Worlds ◽  
Potential Field ◽  
Least Square Method ◽  
Least Square ◽  
Wheelchair Users ◽  
Powered Wheelchair ◽  
Ordinary Least Square ◽  
Assistive Systems

In spite of the presence of powered wheelchairs, some of the users still experience steering challenges and manoeuvring difficulties that limit their capacity of navigating effectively. For such users, steering support and assistive systems may be very necessary. To appreciate the assistance, there is need that the assistive control is adaptable to the user’s steering behaviour. This paper contributes to wheelchair steering improvement by modelling the steering behaviour of powered wheelchair users, for integration into the control system. More precisely, the modelling is based on the improved Directed Potential Field (DPF) method for trajectory planning. The method has facilitated the formulation of a simple behaviour model that is also linear in parameters. To obtain the steering data for parameter identification, seven individuals participated in driving the wheelchair in different virtual worlds on the augmented platform. The obtained data facilitated the estimation of user parameters, using the ordinary least square method, with satisfactory regression analysis results.

Computer Aided Regression Analysis of Synergistic Effect of Energy Industry

2014 ◽  
Vol 543-547 ◽  
pp. 4667-4670
Author(s):  
Jiong Wei Chen ◽  
Guo Ping Cheng
Keyword(s):  
Economic Development ◽  
Regression Analysis ◽  
Linear Regression ◽  
Synergistic Effect ◽  
Linear Correlation ◽  
Least Square Method ◽  
Least Square ◽  
Energy Industry ◽  
Computer Aided ◽  
Industry Investment

In this paper, we try to find out the synergistic effect between energy industry investment and economic development. Based on the objective, with computer aided method, we choose the statistic data of energy industry investment and GDP of China from 2001 to 2011, use econometrics software Eviews 5.0 and least square method to build the linear regression model between energy industry investment and GDP. The result shows that there exists a linear correlation between energy industry investment and GDP; moreover, energy industry investment is more influential than the GDP.

Nonlinear Regression Analysis for Programming and Engineering Application

2013 ◽  
Vol 846-847 ◽  
pp. 1080-1083
Author(s):  
Qing Lan Qi ◽  
Shao Xiong Zhang
Keyword(s):  
Mathematical Model ◽  
Regression Analysis ◽  
Nonlinear Regression ◽  
Regression Coefficient ◽  
Engineering Application ◽  
Least Square Method ◽  
Least Square ◽  
Nonlinear Regression Analysis ◽  
Practical Engineering ◽  
The Mathematical Model

Aiming at the calculating the flow of cutthroat flume in Hydraulic Engineering, the test data is processed through the nonlinear regression analysis program which is based on the principle of least square method. With 33 equations of various functions including linear, power function curve and exponential curve to be selected as the mathematical model, the regression analysis is taken through 33 equations. Comparing the regression coefficient from analysis, the optimal mathematical model is selected as the empirical formula, which has great significance in guiding the practical engineering.

Statistical Analyses of Physical Mechanics (PM) Indexes of Zhejiang Soft Soil

2011 ◽  
Vol 261-263 ◽  
pp. 1674-1678
Author(s):  
Jun Ying Guo ◽  
Rong Ji Li ◽  
Hui Fang Shen
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Correlation ◽  
Soft Soil ◽  
Least Square Method ◽  
Soil Samples ◽  
Least Square ◽  
Statistical Regression ◽  
Regression Analyses ◽  
Physical Mechanics

Through mathematical statistics analyses of basic PM indexes of Zhejiang soft soil samples, obtained are the statistics of soft soil PM parameters, and hence its engineering geological quality. Through linear regression analyses of the soft soil PM indexes by least square method, obtained is the formula of linear inter-index correlations, and tested is the significance between the linear correlation and parameters. The outcomes of the statistical regression analysis provide reference for a rough inter-calculation among soft soil PM indexes, and for engineering constructions.

scholarly journals Employment and foreign direct investment

2018 ◽  
Vol 69 (5) ◽  
pp. 552-570
Author(s):  
Ana Gardašević
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Time Series Data ◽  
Econometric Model ◽  
Statistical Significance ◽  
Least Square Method ◽  
Least Square ◽  
Series Data ◽  
Foreign Direct Investments ◽  
Total Structure

The purpose of this study is to examine and better understand the effects of foreign direct investments on employment in Montenegro over the period from 2005-2017. Time series data on a quarterly basis, obtained from Central Bank of Montenegro, Statistical Office of Montenegro - MONSTAT and Employment Office of Montenegro were used in this research. To perform time series stationary testing, Dickey-Fuller test (ADF) and Perron test were used, i.e. the unit root tests, while the examination of the effects of foreign direct investments on employment was performed using the regression analysis with the least square method. The results of the research, obtained by the evaluation of the simple linear econometric model show that if foreign direct investments increase by 1%, employment in Montenegro can be expected to increase by an average of 0.0058%. However, the regression analysis results clearly show that over the total observed period, the influence of foreign direct investments on employment does not have statistical significance. The obtained results are not surprising, considering the fact that the observed period is characterized by a modest share of the greenfield investment within the total structure of foreign direct investments in the Montenegrin economy.

The Rebound Curve Research of Inspection the High Strength Concrete

2012 ◽  
Vol 446-449 ◽  
pp. 3239-3242
Author(s):  
Hai Bin Chen ◽  
Hui Dong Lu ◽  
Nan Ge ◽  
Xiao Jun Tong
Keyword(s):  
Regression Analysis ◽  
High Strength Concrete ◽  
Concrete Strength ◽  
High Strength ◽  
Least Square Method ◽  
Least Square ◽  
Concrete Technology ◽  
Strength Concrete ◽  
Detection Technology ◽  
Analysis Theory

Since the nineteen nineties, high strength concrete technology was developing rapidly in our country. However, high-strength concrete detection technology is relatively backward. According to the characteristic of the pumping concrete in Tangshan area and the requirements of JGJ/T23-2001, The paper adopted representative materials of Tangshan to divide high strength concrete test blocks which strength grade is from C50 to C80 into 4 ages of 14 days, 28 days, 60 days and 90 days, then adopted high strength concrete rebound apparatus to experimental research by the rebound method. At last, the test data was collected, and applied regression analysis theory, then used the principle of least square method for regression analysis. The optimal pumping concrete strength rebound curve formula could be obtained.

scholarly journals FAKTOR – FAKTOR YANG MEMPENGARUHI TINGKAT PENGGANGGURANDI PROVINSI SULAWESI UTARA

2017 ◽  
Vol 13 (1A) ◽  
pp. 55
Author(s):  
Arfan ., Poyoh ◽  
Gene H. M. Kapantow ◽  
Juliana R. Mandei
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Least Square Method ◽  
Least Square ◽  
Gdp Growth ◽  
Affecting Factors ◽  
Factors Affecting ◽  
Ordinary Least Square ◽  
North Sulawesi

The study aims to analyze the factors - factors affecting the level of unemployment in theprovince of North Sulawesi. These factors include wages, inflation and GDP growth. This study usesmultiple linear regression analysis with Ordinary Least Square method (OLS) was performed using14 years data from 2001 to 2014. The results showed wage variables significantly influence theunemployment rate in North Sulawesi province with probability 0.0104, while inflation and levels ofGDP growth does not significantly influence the unemployment rate with respective probabilities0.5619 for Inflation and 0.3791 for GDP growth.Keywords: affecting factors, wages, inflation, GDP growth, unemployment, North Sulawesi Province

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