scholarly journals Efficiency Improvement for Ordinary Least Square and Orthogonal Regression-An Application in Chemical Engineering

2019 ◽  
pp. 1-5
Author(s):  
Khurshid A. Bhat
Keyword(s):  
Regression Models ◽  
Chemical Engineering ◽  
Error Component ◽  
Least Square ◽  
Future Research ◽  
Engineering Science ◽  
Efficiency Improvement ◽  
Research Projects ◽  
Ordinary Least Square ◽  
Best Fit

Regression analysis plays indispensable role in QSAR/QSPR, chemical Engineering, science & technology and research projects. Best fit regression models are constantly a challenge to the researchers, efforts are taken to minimize the error components so that the predictability and efficiency of models increase. Presence of high error component eventually upset the future research and forecasting of the facts. In this paper a technique is introduced that reduces the error component and improves the predictability and efficiency of the model.

scholarly journals KAJIAN METODE ORDINARY LEAST SQUARE DAN ROBUST ESTIMASI M PADA MODEL REGRESI LINIER SEDERHANA YANG MEMUAT OUTLIER

2020 ◽  
Vol 11 (1) ◽  
pp. 21
Author(s):  
Zahrotul Aflakhah ◽  
Jajang Jajang ◽  
Agustini Tripena Br. Sb.
Keyword(s):  
Full Article ◽  
Regression Model ◽  
Sample Size ◽  
Regression Models ◽  
Estimation Method ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Simple Linear Regression ◽  
Ordinary Least Square ◽  
M Estimation

This research discusses about the Ordinary Least Squares (OLS) method and robust M-estimation method; compare between the Tukey bisquare and Huber weighting from simple linier regression models that contain outliers. Data are generated through simulation with the percentages of outliers and sample sizes. Each data will be formed into a simple linier regression model, then the percentage of outliers, RSE and MAD values are calculated. The results show that RSE and MAD values produced by a simple linear regression model with the OLS method are influenced by the percentage of outliers. However, the regression model of robust M-estimation with sample size 30, 60, 90, 120, and 150 results an unstable RSE values with the change of the percentage of outlier and the MAD values that are not affected by the percentage of outliers and sample size. The robust M-estimation method with Tukey Bisquare weighting is as good as the Huber weighting. Full Article

Understanding IFRS adoption

2019 ◽  
Vol 20 (4) ◽  
pp. 543-570 ◽  
Author(s):  
Olfa Riahi ◽  
Walid Khoufi
Keyword(s):  
Logistic Regression ◽  
Least Square ◽  
Future Research ◽  
Behavioral Factors ◽  
Content Type ◽  
Ordinary Least Square ◽  
Ifrs Adoption ◽  
Starting Point ◽  
Behavioral Attribute ◽  
The Impact

Purpose The purpose of this paper is to discern the impact of main behavioral factors that could affect the decision of adopting IFRS in developing countries (DCs). In other words, this work looks to identify the different variables that are likely to influence the adoption of IFRS in these countries. Design/methodology/approach The methodological orientation of this research is to highlight and analyze the correlation between the cited factors and the IFRS adoption in DCs. Tested models are functions of logistic regression. To assess the parameters of these functions, the commonly used method is not that of ordinary least square but the maximum likelihood technique. In short, this study followed a hypothetical-deductive methodology by referring to the application of a logistic regression for each of the variables presumed to be analyzed. The authors implement this empirical model by using the neo-institutional approach and basing on a sample of 108 DCs. Findings The empirical results show that there exists a bidirectional causal relationship between the majority of the developed behavioral variables and the decision of whether adopting or unadopting IFRS by DCs. They also indicate through multivariate analysis that the selection of IFRS by DCs is primarily legitimized by institutional and social pressures (institutional isomorphism). Research limitations/implications It is essential to indicate that some limits might be assigned to the study. They are attached principally to the use of a dichotomous dependent variable which presents a restriction in a sense where the robust inequality at the level of the numbers of the countries of sub-samples can relatively weaken the findings. There are also few studies that jointly analyze the behavioral dimensions within a country and the adoption of IFRS. Institutional theory emanated from the research has proved useful in escaping this limit. Practical implications These empirical insights are of particular interest to local accounting standard setters of the selected countries since they can provide a better discernment of factors that can encourage the adoption of IFRS. Indeed, the research can be a reference for governments to better identify the economic, political and institutional obstacles that have an impact on behaviors which could compel countries to flee the adoption of IFRS. This paper will also be helpful for future research studying the links between human behavior and accounting in a general way. It should be noted that the results will be significant for future studies looking for real behavioral factors that drive a country to adopt an accounting framework. The studies will be able to use the empirical variables as a starting point and then they can extract new measures to identify the impact of behavior on decisions to adopt any standards. Originality/value At the present study, the authors strive to provide input to the literature by focusing on the determinants of the choice of an accounting practice in a DC reverberating to a new dimension which is the behavioral attribute.

Understanding the determinants of festival attendee spending: the role of cultural capital

2020 ◽  
Vol 11 (2) ◽  
pp. 145-159 ◽  
Author(s):  
Andrea Báez-Montenegro ◽  
María Devesa
Keyword(s):  
Cultural Capital ◽  
Regression Models ◽  
Least Square ◽  
Tobit Regression ◽  
Content Type ◽  
Ordinary Least Square ◽  
The City ◽  
Practical Implications

PurposeThe purpose of this paper is to explore which factors determine visitor spending at a cultural festival, focusing particularly on cultural capital variables.Design/methodology/approachThe case study is the Valdivia International Film Festival. Data from a survey conducted amongst a representative sample of attendees at the festival is used and ordinary least square (OLS) and Tobit regression models are applied.FindingsSix of the variables included from the model prove statistically significant: gender, age, place of residence, participation in other activities at the festival, and “leisure and sharing” motivation.Practical implicationsFestival organisers should draw up a programme and prepare activities that are balanced so as to attract local film lovers, but that should also appeal to outside visitors, who would see the festival as an opportunity to enjoy a wider tourist experience, all of which would have a broader economic impact on the city.Originality/valueUnderstanding which factors determine spending leads to an improvement in the event's viability and ensures its future sustainability. This study adds to the growing literature establishing a sound theoretical corpus on the topic.

Which personal values matter most? Job performance and job satisfaction across job categories

2019 ◽  
Vol 27 (1) ◽  
pp. 109-124 ◽  
Author(s):  
Hussein N. Ismail ◽  
Silva Karkoulian ◽  
Sevag K. Kertechian
Keyword(s):  
Job Satisfaction ◽  
Job Performance ◽  
Personal Values ◽  
Partial Least Square ◽  
Least Square ◽  
Future Research ◽  
Content Type ◽  
Ordinary Least Square ◽  
Different Types ◽  
The Relationship

PurposeAs one of the first studies in this field, the purpose of this paper is to explore the effect of personal values on job performance and job satisfaction across different jobs. Further, it aims to identify personal value types that are positively, or negatively, related to behavioural and attitudinal outcomes in different job categories.Design/methodology/approachBased on a sample of 270 participants across several job categories including finance, accounting, marketing, sales, HR (human resources), operations and information technology (IT), this research explores the relationship between personal values, job performance and job satisfaction across the listed job categories. Ordinary least square (OLS) stepwise-regression and partial least square (PLS) regression were used in analysing the results.FindingsFindings showed that for some of the jobs examined, different types of personal values were associated with different worker outcomes.Originality/valueThis research study identifies sets of personal values that are suited to some jobs more than others in terms of job performance and job satisfaction outcomes. Moreover, this research demonstrates the importance of controlling for job categories in future research models that investigate the links between values, performance and satisfaction.

scholarly journals Impor gandum Indonesia dan faktor-faktor yang Mempengaruhinya

2019 ◽  
Vol 7 (2) ◽  
pp. 101-112
Author(s):  
Gita Wulandari ◽  
Siti Hodijah ◽  
Yohanes Vyn Amzar
Keyword(s):  
Gross Domestic Product ◽  
Interest Rates ◽  
Regression Models ◽  
Total Population ◽  
Secondary Data ◽  
Least Square ◽  
Domestic Product ◽  
Linear Regression Models ◽  
Ordinary Least Square ◽  
Multiple Linear Regression Models

This study aims: 1) to analyze the development of wheat import volume, gross domestic product (GDP), inflation, investment credit interest rates, and population of Indonesian wheat imports. 2) to analyze the effect of gross domestic product, inflation, investment interest rates on Indonesian wheat imports. This study is a descriptive study and the types of data used in this study are secondary data in the form of gross domestic product, inflation, investment credit interest rates, and population for the last 18 years (2000-2017). The data obtained were processed using SPSS 20 with multiple linear regression models using the Ordinary Least Square (OLS) method. The results of this study indicate that the gross domestic product (GDP) obtained a significant level of 0.03, inflation obtained a significant level of 0.598, and the total population obtained a significant level of 0.522. The regression results show that partially only the variable gross domestic product (GDP) and interest rates are Investment credit interest has a significant effect on imports of Indonesian wheat, while inflation and population have no significant effect on imports of Indonesian wheat. Keywords: GDP, Inflation, Interest rates, Population

scholarly journals Impact of socio-economic and water access conditions on life satisfaction of rural farmers in Faisalabad district of Pakistan

Water Policy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 686-701
Author(s):  
Abdul Majeed Nadeem ◽  
Muhammad Zahid Rafique ◽  
Khuda Bakhsh ◽  
Muhammad Sohail Amjad Makhdum ◽  
Shaoan Huang
Keyword(s):  
Life Satisfaction ◽  
Water Supply ◽  
Rural Areas ◽  
Well Being ◽  
Least Square ◽  
Future Research ◽  
Water Access ◽  
Economic Activities ◽  
Ordinary Least Square ◽  
Farming Community

Abstract The current study is designed to see the effects of water access on the well-being of the farming community in rural areas of Pakistan. The data were collected from 300 households of ten villages in rural Faisalabad, Pakistan where the population is facing serious water quality and access issues due to industrial pollution, lack of clean water supply system and limited access to fresh water for agricultural use. We employed ordinary least square and ordered probit methods to measure the association between water access variables and households’ well-being. We found that source and quality of drinking water, access to irrigation water, and percentage of crop water requirement fulfilled, and water expenses were statistically significant influencing the households’ well-being. The study concluded that water access conditions strongly influence the life satisfaction and water access conditions must be considered in future research. Acknowledging the contribution of village-level economic activities to economic growth, a strong policy is proposed to re-evaluate the existing rural water supply strategy to enhance the households’ well-being and enhance livelihood generation among neglected pro-poor farmers in rural areas of Pakistan.

scholarly journals The Effect of Industrial Sector and Transportation Sector on CO2 Emissions In Indonesia

2021 ◽  
Vol 6 (1) ◽  
pp. 56
Author(s):  
Izmi Dwi Maharani Poetri
Keyword(s):  
Co2 Emissions ◽  
Environmental Quality ◽  
Carbon Dioxide Emissions ◽  
Regression Models ◽  
Industrial Sector ◽  
Least Square ◽  
Linear Regression Models ◽  
Ordinary Least Square ◽  
Transportation Sector ◽  
Positive Effect

<p><em>Environmental quality is an important aspect of life.</em><em> </em><em>This study aims to analyze the effect of industrial sector GDP and transportation sector GDP on environmental quality in terms of carbon dioxide emissions in Indonesia.</em><em> </em><em>This analysis uses multiple linear regression models with the Ordinary Least Square (OLS) method.</em><em> </em><em>The results of the analysis show that the GDP of the Industrial Sector has no significant effect on CO2 emissions, while Transportation GDP has a significant and positive effect on CO2 emissions, this is supported by the Environmental Kuznet Curve (EKC) theory.</em><em></em></p><p><strong><em> </em></strong></p><p><strong><em>Keywords</em></strong><em> : carbondioxyde emission, GDP of industry sector, GDP of transportation sector </em></p>

scholarly journals Impact of Inflation and Unemployment on Economic Growth of Pakistan

2021 ◽  
Vol 6 (4) ◽  
pp. 282-288
Author(s):  
Muhammad Ramzan
Keyword(s):  
Economic Growth ◽  
Diagnostic Tests ◽  
Regression Models ◽  
Error Term ◽  
Least Square ◽  
Linear Regression Models ◽  
Ordinary Least Square ◽  
White Test ◽  
Multiple Linear Regression Models

This paper aims to identify the influence of inflation and unemployment on the economic growth of the country. This study recommends some essential policies about unemployment and inflation in the economic growth of Pakistan. In this study, the “Ordinary Least Square (OLS)” method is used with different diagnostic tests for determining the fitness of data for the investigation; and the data is collected from 1980 to 2018. The econometric results suggest that the time series is stationary because the values of t-statistic are more than t-tab and sig value is also significant. The error term on ADF is significant and that ensures that there is long term association. The results of ECM indicate that inflation and unemployment are away from the value of equilibrium. The results of multiple linear regression models indicate that inflation and unemployment are statistically insignificant, and the overall model is also statistically insignificant. There is no multicollinearity and there is no heteroscedasticity as per White test. By running the Ramsay Reset test, the researcher concludes that the model is not specified because the sig value of the t-test and f-test is significant.

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