scholarly journals Mean Estimators Using Robust Quantile Regression and L-Moments’ Characteristics for Complete and Partial Auxiliary Information

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Malik Muhammad Anas ◽  
Zhensheng Huang ◽  
David Anekeya Alilah ◽  
Ambreen Shafqat ◽  
Sajjad Hussain
Keyword(s):  
Quantile Regression ◽  
Auxiliary Information ◽  
Simple Random Sampling ◽  
Least Square ◽  
R Language ◽  
Ordinary Least Square ◽  
Numerical Studies ◽  
Regression Estimators ◽  
L Moments ◽  
Class Of Estimators

Ratio type regression estimator is a prevalent and readily implemented heuristic under simple random sampling (SRS) and two-stage sampling for the estimation of population. But this existing method is based on the ordinary least square (OLS) regression coefficient which is not an effective approach in the presence outliers in the data. In this article, we proposed a class of estimators firstly for complete auxiliary information and, later on, for partial auxiliary information for the presence of outliers in the data. To address this problem, initially we presented a distinct class of estimators by introducing the characteristics of L-moments in the existing estimators. Later on, quantile regression estimators are defined as more robust in the presence of outliers. These techniques empowered the proposed estimators to handle the problem of outliers. To prove the better performance of the proposed estimators, numerical studies are carried out using R language. To calculate the mean square error (MSE), hypothetical equations are expressed for adapted and proposed estimators. Percentage Relative Efficiencies (PRE) are compared to justify the proposed estimators.

Socio demographic determinants of BMI of Pakistani women: an evidence from PDHS (2017-18) using quantile regression analysis

2021 ◽  
Author(s):  
Asifa Kamal ◽  
Aqsa Asghar Ali ◽  
Sameena Irfan
Keyword(s):  
Quantile Regression ◽  
Economic Status ◽  
Household Head ◽  
Secondary Data ◽  
Wealth Index ◽  
Least Square ◽  
Obese Women ◽  
Ordinary Least Square ◽  
Under Nutrition ◽  
Pakistani Women

Abstract Objective: To explore the socio demographic determinants of nutritional status of Pakistani women. Methods: Secondary data from recent Pakistan Demographic and Health Survey (PDHS 2017-18) is taken. Data collection period is from 22 November 2017 to 30 April 2018. Ordinary least square (OLS) and quantile regression (QR) models are used for analysis. Results: QR model is found appropriate for BMI data to capture effect at different level of distribution of BMI. Less than 5% women are under nutrition for some categories of factors. Age of women, women’s education, frequency of watching TV, wealth index, husband’s education and region (KPK, Balochistan) showed a positive effect on women’s BMI in Pakistan across all conditional distribution of BMI. In contrary, age of women at first birth, women’s agriculture or manual working status, gender of household head (female) and region (Sindh) showed negative effect on women’s BMI in Pakistan. Conclusion: It is concluded that overweight/obesity is becoming serious problem as compared to undernutrition in Pakistani women. Percentage of deprived women is little and level of under nutrition is also not alarming.  Privileged women (with respect to education, economic status, urbanization, sedentary life style) have more chances to have higher BMI (overweight or obese). Women of KPK and Balochistan are at higher risk of overweight/ obesity as compared to Punjabi women. Keywords: PDHS 2017-18, Ordinary Least Square (OLS), Quantile Regression (QR) Model, Continuous....

scholarly journals Determinants of Common Bean (Phaseolus Vulagris L.) Marketed Surplus Among Smallholder Farmers in Humbo and Damot Gale Woredas, Southern Ethiopia

2018 ◽  
Vol 2 (1) ◽  
pp. 20
Author(s):  
Besufekad Belayneh ◽  
Tewodros Tefera ◽  
Thomas Lemma
Keyword(s):  
Common Bean ◽  
Smallholder Farmers ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Least Square ◽  
Primary Data ◽  
Southern Ethiopia ◽  
Cross Sectional ◽  
Ordinary Least Square ◽  
Multi Stage

This research was aimed to study the common bean (Phaseolus vulagris L.) marketed surplus among smallholder farmers in the Humbo and Damot Gale Woredas. A multi-stage sampling technique was used in order to determine the sample respondents. By using simple random sampling technique four sample Kebeles were selected. Cross sectional data were collected from 182 farm households who produced common bean in 2016 production season. Primary data were collected from sample households using structured questionnaire. Descriptive statistics and econometric model were employed to analyze the data. To identify determinants of marketed surplus of common bean, Ordinary Least Square (OLS) model was employed. The study suggest interventions such as intensification strategies which increase yields through proper management and use of inputs, rural infrastructure improvement increases the likelihood of market orientation and marketed surplus of common bean.

scholarly journals Minimum Covariance Determinant-Based Quantile Robust Regression-Type Estimators for Mean Parameter

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Usman Shahzad ◽  
Nadia H. Al-Noor ◽  
Noureen Afshan ◽  
David Anekeya Alilah ◽  
Muhammad Hanif ◽  
...  
Keyword(s):  
Quantile Regression ◽  
Robust Regression ◽  
Real Life ◽  
Minimum Covariance Determinant ◽  
Mean Squared Errors ◽  
Regression Estimators ◽  
Chi Squared ◽  
Class Of Estimators ◽  
The Mean ◽  
Ratio Estimators

Robust regression tools are commonly used to develop regression-type ratio estimators with traditional measures of location whenever data are contaminated with outliers. Recently, the researchers extended this idea and developed regression-type ratio estimators through robust minimum covariance determinant (MCD) estimation. In this study, the quantile regression with MCD-based measures of location is utilized and a class of quantile regression-type mean estimators is proposed. The mean squared errors (MSEs) of the proposed estimators are also obtained. The proposed estimators are compared with the reviewed class of estimators through a simulation study. We also incorporated two real-life applications. To assess the presence of outliers in these real-life applications, the Dixon chi-squared test is used. It is found that the quantile regression estimators are performing better as compared to some existing estimators.

scholarly journals PERBANDINGAN TRANSFORMASI BOX-COX DAN REGRESI KUANTIL MEDIAN DALAM MENGATASI HETEROSKEDASTISITAS

2015 ◽  
Vol 4 (1) ◽  
pp. 8
Author(s):  
NI WAYAN YUNI CAHYANI ◽  
I GUSTI AYU MADE SRINADI ◽  
MADE SUSILAWATI
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Quantile Regression ◽  
Linear Regression Analysis ◽  
Least Square ◽  
Power Transformation ◽  
Ordinary Least Square

Ordinary least square (OLS) is a method that can be used to estimate the parameter in linear regression analysis. There are some assumption which should be satisfied on OLS, one of this assumption is homoscedasticity, that is the variance of error is constant. If variance of the error is unequal that so-called heteroscedasticity. The presence heteroscedasticity can cause estimation with OLS becomes inefficient. Therefore, heteroscedasticity shall be overcome. There are some method that can used to overcome heteroscedasticity, two among those are Box-Cox power transformation and median quantile regression. This research compared Box-Cox power transformation and median quantile regression to overcome heteroscedasticity. Applied Box-Cox power transformation on OLS result ????2point are greater, smaller RMSE point and confidencen interval more narrow, therefore can be concluded that applied of Box-Cox power transformation on OLS better of median quantile regression to overcome heteroscedasticity.

scholarly journals PENGARUH KUALITAS PELAYANAN KESEHATAN DAN KEPUASAN PASIEN TERHADAP CITRA KLINIK “X” DI TUBAN

2020 ◽  
Vol 8 (2) ◽  
pp. 206
Author(s):  
Andrianto Andrianto ◽  
Cahyo Sasmito ◽  
Cakti Indragunawan
Keyword(s):  
Patient Satisfaction ◽  
Service Quality ◽  
Secondary Data ◽  
Simple Random Sampling ◽  
Least Square ◽  
Primary Data ◽  
Clinical Image ◽  
Validity And Reliability ◽  
Ordinary Least Square ◽  
Normality Test

This study aims to determine and analyze the effect of service quality and patient satisfaction on X Tuban clinical image. Sampling is done by simple random sampling. The number of samples determined was 92 samples. The data used are primary data and secondary data. The analytical method used to determine the effect of service quality and patient satisfaction on the X Tuban Clinic image is multiple linear regression with the Ordinary Least Square (OLS) method. Before a regression is carried out, a validity and reliability test is performed for each question. In addition, a normality test and a classic assumption test are performed. The results showed that the quality of service and patient satisfaction simultaneously and individually affected the positive image of the Tuban X Clinic.

Factors affecting housing prices in Izmir, Turkey: a quantile regression approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Onur Özsoy ◽  
Hasan Şahin
Keyword(s):  
Quantile Regression ◽  
House Prices ◽  
Housing Prices ◽  
Least Square ◽  
Policy Implications ◽  
Content Type ◽  
Factors Affecting ◽  
Ordinary Least Square ◽  
Major Factors ◽  
Quantile Regression Method

Purpose The purpose of this paper is to investigate empirically the main factors that affect the house prices in Izmir, Turkey using the quantile regression and ordinary least square approaches. Design/methodology/approach Sample data about the housing market for Izmir collected from the web pages of various real estate agencies during June 2018. Following this, the quantile regression method is used to estimate all possible effects of variables on each interested quantile to determine the factors that affect house prices to guide the potential consumers, house developers, city planners and the policymakers in Izmir, Turkey. Findings Results show that the age of the house, central heating and parking have no significant effect on prices. The size of the house, the existence of an elevator, fire and security have a positive and significant effect on prices. The number of rooms has lower values for high-priced houses, while the floor, the number of balconies, air conditioning, proximity to schools have a higher value for high-priced houses. The number of toilets, the number of bathrooms and the distance to the hospital have a lower value on the high-priced housing. The value of the distance from the city center and the shopping center is almost uniform in all quantiles and lowers the value of the higher-priced houses. With the exception of the value of the houses in the 10th percentile in Balcova district, the value of the houses in Konak, Balcova and Narlidere is lower prices in Karsiyaka. Originality/value This is the first comprehensive research to determine the major factors that affect house prices in Izmir. The second contribution of this paper is that it includes all possible variables and accordingly derives adequate policy implications, which could be used both by the public housing authority and private housing constructing companies in designing and implementing effective housing policies.

scholarly journals Development of Estimation Procedure of Population Variance in Stratified Randomized Response Technique

2020 ◽  
pp. 1-8
Author(s):  
Nadia Mushtaq ◽  
Iram Saleem
Keyword(s):  
Variance Estimation ◽  
Auxiliary Information ◽  
Estimation Procedure ◽  
Randomized Response Technique ◽  
Randomized Response ◽  
Population Variance ◽  
Regression Estimators ◽  
Class Of Estimators ◽  
Estimation Of Variance ◽  
Sensitive Variable

Singh et al. (2016) presented a ratio and regression estimators of population variance of a sensitive variable using auxiliary information based on randomized response technique (RRT). In this article, the RRT is considered in stratified random sampling for the estimation of variance. A generalized class of estimators of variance in stratified RRT is proposed and derive the procedure of variance estimation in stratified RRT. The expression of the bias and mean square error are expressed. The empirical findings support the soundness of proposed scheme of variance estimation.

scholarly journals COVID-19 and tourism sector: A perspective of Saudi Arabia

2021 ◽  
Vol 8 (9) ◽  
pp. 58-62
Author(s):  
Abeer Shergawi Kernshi ◽  
◽  
Rida Waheed ◽  
Keyword(s):  
Saudi Arabia ◽  
Quantile Regression ◽  
Least Square ◽  
Current Paper ◽  
Ordinary Least Square ◽  
Tourism Sector ◽  
The Relationship

The current paper attempts to analyze the relationship between COVID-19 and tourism in Saudi Arabia from the period 2nd March 2020–15th Nov 2020 as COVID-19 cases started to increase in March 2020. Along with this, predicted data is also used for the year 2021 in order to know the situation of tourism in the coming year if COVID-19 cases continue to increase. Ordinary least square, as well as quantile regression, is used to have a detailed overview of the nexus between COVID-19 and tourism. The findings of the study clearly indicate that tourism in Saudi Arabia is declined significantly due to COVID-19 in 2020. Besides this, it is also found that if COVID-19 cases continue to increase in 2021, then tourism will continue to decrease in the coming year as well.

scholarly journals Abnormal Audit Delay and Earnings Quality in Nigerian Banking

2018 ◽  
Vol 2 (2) ◽  
pp. 99
Author(s):  
Alexander Olawumi Dabor ◽  
Benjamin David Uyagu
Keyword(s):  
Banking Sector ◽  
Earnings Quality ◽  
Negative Relationship ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Statistical Technique ◽  
Least Square ◽  
Ordinary Least Square ◽  
The Relationship ◽  
Nigerian Banking

The objective of this study is to ascertain the relationship abnormal audit delay and earnings quality in the Nigeria. The study focused on the Nigerian banking sector. The Ordinary Least Square statistical technique was adopted. Eleven banks were selected using the simple random sampling technique. The period under review is eleven years from 2005-2015. The results showed that earnings quality has a negative relationship with abnormal audit delay. The study recommended that management should be prohibited from constant changing of accounting calculation that can cause material discrepancy between the auditor and client regarding accounting practices. 

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