Comparison of ordinary least square and mixed-effect regression models for estimation of tree diameter increment

2015 ◽  
Author(s):  
Suriyati Harun ◽  
Yasmin Yahya ◽  
Nurashikin Saaludin ◽  
Wan Suriyani Che Wan Ahmad
Keyword(s):  
Regression Models ◽  
Least Square ◽  
Mixed Effect ◽  
Ordinary Least Square ◽  
Tree Diameter ◽  
Diameter Increment ◽  
Effect Regression

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

Application of Mixed-Effect Regression Models for Compiling a Land Value Map

2018 ◽  
Author(s):  
Radoslaw Cellmer ◽  
Aneta Cichulska ◽  
Malgorzata Renigier-Bilozor ◽  
Andrzej Bilozor
Keyword(s):  
Regression Models ◽  
Land Value ◽  
Mixed Effect ◽  
Effect Regression

scholarly journals Assessing factors affecting FDI in developing Asian countries

2021 ◽  
Vol 9 (2) ◽  
pp. 16-28
Author(s):  
P. Gupta
Keyword(s):  
Random Effect ◽  
Least Square ◽  
Market Size ◽  
Asian Countries ◽  
Factors Affecting ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Fixed Capital Formation ◽  
Effect Regression ◽  
Independent Variable

The paper focuses on various factors that affect the inflow of Foreign Direct Investment in developing countries. The study majorly deals with Asian countries, namely India, China, Myanmar, Nepal, Pakistan, Bangladesh and Bhutan, that are progressing from being aid-dependent to trading giants. The factors affecting FDI are majorly categorised into dependent and independent variables. Here, in this study, the dependent variable considered is FDI inflow, and independent variables are market size, the value of the currency, export, import, gross fixed capital formation, GDP deflator, cost of borrowing and economic reforms. Pooled Ordinary Least Square (OLS), fixed effect and random effect regression analysis is done to ascertain the best regression model and various tests are performed to check the intensity of effect caused by each independent variable on our dependent variable.

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.

scholarly journals Corporate Social Responsibility and Financial Performance of Hotels in Zanzibar

2019 ◽  
pp. 1-8
Author(s):  
Zuhura Mohamed Abdallah ◽  
Fatma Ali Mohamed
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Financial Performance ◽  
Random Effect ◽  
Least Square Method ◽  
Least Square ◽  
Ordinary Least Square ◽  
Effect Regression ◽  
Corporate Social ◽  
Positive Effect

Corporate Social Responsibility is gaining more awareness in Zanzibar as the firms are recognizing the important role it plays on firm’s performance. This research empirically examines the effect of corporate social responsibility and financial performance of hotels in Zanzibar. CSR is measured by cost paid for corporate social responsibility while financial performance is measured by using profitability measures such as ROA and ROE. By utilizing panel data of 4 hotels for 7 years period from 2011-2017, the study uses ordinary least square method-random effect regression, model. The study found CSR has a significant positive effect on ROA and ROE of hotels in Zanzibar. The study also found that control variables (i.e leverage, R & D, size) have a significant effect on ROA and ROE. The study recommends more investment in CSR as a way of boosting hotels profitability.

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 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>

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