scholarly journals Application of Robust Estimation Methods for the Analysis of Outlier Measurements / Aplikácia Robustných Odhadovacích Metód Pri Analýze Odľahlých Meraní

2011 ◽  
Vol 57 (3) ◽  
pp. 14-29
Author(s):  
Silvia Gašincová ◽  
Juraj Gašinec ◽  
Gabriel Weiss ◽  
Slavomír Labant
Keyword(s):  
Linear Programming ◽  
Least Squares ◽  
Robust Estimation ◽  
Mathematical Analysis ◽  
Physical Environment ◽  
Regression Line ◽  
Measured Data ◽  
Estimation Methods ◽  
Method Of Least Squares ◽  
The Impact

Abstract The basis of mathematical analysis of geodetic measurements is the method of least squares (LSM), whose bicentenary we celebrated in 2006. In geodetic practice, we quite often encounter the phenomenon when outlier measurements penetrate into the set of measured data as a result of e.g. the impact of physical environment. That fact led to modifications of LSM that have been increasingly published mainly in foreign literature in recent years. The mentioned alternative estimation methods are e.g. robust estimation methods and methods in linear programming. The aim of the present paper is to compare LSM with the robust estimation methods on an example of a regression line.

CHOOSING A METHOD FOR ESTIMATING THE PARAMETERS OF LINEAR REGRESSION BASED ON IDENTIFICATION OF ANOMALOUS OBSERVATIONS

2021 ◽  
pp. 24-29
Author(s):  
С.И. Носков
Keyword(s):  
Parameter Estimation ◽  
Least Squares ◽  
Robust Estimation ◽  
Regression Models ◽  
Regression Line ◽  
Estimation Method ◽  
Model Parameters ◽  
Method Of Least Squares ◽  
Sharp Drop ◽  
Modulus Method

Описываются свойства методов оценивания параметров регрессионных моделей - наименьших квадратов, модулей, антиробастного, а также их применения для решения конкретных практических проблем. При этом метод наименьших модулей не реагирует на аномальные наблюдения выборки, метод антиробастного оценивания сильно отклоняет линию регрессии в их направлении, метод наименьших квадратов занимает промежуточное положение. Показано, что если целью построения модели является проведение на ее основе многовариантных прогнозных расчетов значений зависимой переменной, то выбор метода численной идентификации параметров модели следует производить на основе анализа характера выбросов. Если есть основания полагать, что подобные им ситуации могут иметь место в будущем, следует выбрать метод антиробастного оценивания, в противном же случае - метод наименьших модулей. Построена регрессионная модель грузооборота Красноярской железной дороги на основе применения всех трех методов оценивания параметров. Проведен анализ причин, имеющих место в 2010 году в ситуации резкого падения величины грузооборота, которая вполне может характеризоваться как аномальное наблюдение в данных. Сделаны рекомендации по выбору метода оценивания параметров в этом случае The article describes the properties of methods for estimating the parameters of regression models - least squares, moduli, anti-robust - as well as their application for solving specific practical problems. At the same time, the method of least modules does not respond to anomalous observations of the sample, the method of anti-robust estimation strongly deviates the regression line in their direction, the method of least squares occupies an intermediate position. I show that if the purpose of constructing a model is to carry out multivariate predictive calculations of the values of the dependent variable on its basis, then the choice of a method for the numerical identification of model parameters should be based on an analysis of the nature of emissions. If there is a reason to believe that similar situations may occur in the future, the anti-robust estimation method should be chosen, otherwise - the least modulus method. I built a regression model of the freight turnover of the Krasnoyarsk railway on the basis of the application of all three methods of parameter estimation. I carried out the analysis of the reasons for the situation of a sharp drop in the value of cargo turnover in 2010, which may well be characterized as anomalous observation in the data. I give recommendations on the choice of the parameter estimation method in this case

The impact of gender inequality in education and employment on economic performance in Turkey: evidence from a cointegration approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ömer Esen ◽  
Gamze Yıldız Seren
Keyword(s):  
Least Squares ◽  
Economic Performance ◽  
Ordinary Least Squares ◽  
Estimation Methods ◽  
Content Type ◽  
Cointegration Tests ◽  
Johansen Cointegration ◽  
Education And Employment ◽  
The Impact

PurposeThis study aims to empirically examine the impact of gender-based inequalities in both education and employment on economic performance using the dataset of Turkey for the period 1975–2018.Design/methodology/approachThis study employs Johansen cointegration tests to analyze the existence of a long-term relation among variables. Furthermore, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) estimation methods are performed to determine the long-run coefficients.FindingsThe findings from the Johansen cointegration analysis confirm that there is a long-term cointegration relation between variables. Moreover, DOLS and FMOLS results reveal that improvements in gender equality in both education and employment have a strong and significant impact on real gross domestic product (GDP) per capita in the long term.Originality/valueThe authors expect that this study will make remarkable contributions to the future academic studies and policy implementation, as it examines the relation among the variables by including the school life expectancy from primary to tertiary based on the gender parity index (GPI), the gross enrollment ratio from primary to tertiary based on GPI and the ratio of female to male labor force participation (FMLFP) rate.

Wool follicle development in the New Zealand Romney and N type sheep. I. The relationships of development to age in the New Zealand Romney and N type sheep foetuses and a comparison with results obtained from the Merino

1957 ◽  
Vol 8 (4) ◽  
pp. 371 ◽  
Author(s):  
SK Stephenson
Keyword(s):  
New Zealand ◽  
Least Squares ◽  
Linear Relationship ◽  
Population Studies ◽  
Regression Line ◽  
The Body ◽  
Follicle Development ◽  
Method Of Least Squares ◽  
Rate Of Development ◽  
Wool Follicle

The development of the follicle population in New Zealand Romney and N-type sheep foetuses has been studied by comparing stages of development at different ages, using the method developed by Carter and Hardy (1947) and Hardy and Lyne (1956). Their scale has been altered so as to give a linear relationship with age, and a regression line has been fitted to the data by the method of least squares. Analysis of the N-type and New Zealand Romney mating groups and a comparison with the Merino data given by Carter and Hardy (1947) show that no marked or consistent differences occur in the age at which different stages of follicle development are completed or in the rate of development of the follicle population. Studies of different positions on the body agree with the findings of other workers that development begins first on the head and limbs and later over the trunk. Between positions the correlation between the age at which follicle development begins and the rate of development after initiation is not significant.

Comparison of the Method of Least Squares and the Simplex Method for Processing Geodetic Survey Results / Porovnanie Metódy Najmenších Štvorcov A Simplexovej Metódy Pri Spracovaní Výsledkov Geodetických Meran

2013 ◽  
Vol 59 (3) ◽  
pp. 21-36
Author(s):  
Silvia Gašincová ◽  
Juraj Gašinec
Keyword(s):  
Linear Programming ◽  
Least Squares ◽  
Minimization Problem ◽  
Simplex Method ◽  
Optimal Solution ◽  
Geodetic Survey ◽  
Tabular Form ◽  
Method Of Least Squares ◽  
Geodetic Measurements ◽  
Survey Results

Abstract The present paper is devoted to the use of the simplex method in the processing of results from geodetic measurements as compared with the standard used method of least squares. Using the simplex method, a minimization problem is usually solved in a standard tabular form by rearranging lines and columns in order to find an optimal solution. The paper points out the simpler, more stable and more efficient way to solve a problem of linear programming through a matrix of relations.

scholarly journals Techniques for dealing with discordant observations

1986 ◽  
Vol 114 ◽  
pp. 229-231
Author(s):  
Richard L. Branham
Keyword(s):  
Solar System ◽  
Least Squares ◽  
Robust Estimation ◽  
Method Of Least Squares ◽  
Astronomical Data ◽  
Solar System Objects ◽  
Observational Errors ◽  
Normally Distributed

To test any theory such as theories of motion–Newtonian or relativistic–of solar system objects, one must compare the predictions of theory with observation. But discordant observations habitually plague the reducer of astronomical data. To alleviate the baleful effects, particularly harmful when the observations are reduced by the method of least squares, of discordant data investigators almost invariably reject observations whose corresponding (0-C)'s or post-solution residuals exceed a cutoff. But techniques that are insensitive to the assumption that the observational errors are normally distributed, called robust estimation in the literature, have also been developed.

Robust Estimation Peculiarity of Robust Estimation Methods in Observations to Obey Generalized Gaussian Distribution

2014 ◽  
Vol 556-562 ◽  
pp. 4380-4385
Author(s):  
Peng Fei Xing ◽  
Yong Hui Ge ◽  
Yan Li
Keyword(s):  
Robust Estimation ◽  
Gaussian Distribution ◽  
Estimation Method ◽  
Simulation Method ◽  
Estimation Methods ◽  
Generalized Gaussian Distribution ◽  
The Impact

Robust estimation method in generalized Gaussian distribution of observations under obedience can effectively eliminate or reduce the influence of gross errors, however, peculiarity of different estimation methods are not the same. In this paper, it’s used simulation method, the commonly used 13 kinds of robust features robust estimation methods were compared. The results showed that: L1 method, Danish method, German-McClure method and IGGIII program is more efficient robust estimation methods in Observations to obey generalized gaussian distribution, which method is more effective than other commonly used to eliminate the impact of robust estimation of gross errors or weaken .

scholarly journals Application of robust estimation methods to simple models of nucleon separation energies

2015 ◽  
Vol 30 (24) ◽  
pp. 1550121
Author(s):  
S. Baselga
Keyword(s):  
Least Squares ◽  
Robust Estimation ◽  
Estimation Methods ◽  
Quality Of Data ◽  
Estimated Parameters ◽  
Complex Models ◽  
The Stability ◽  
Experimental Values ◽  
Simple Models

Some works have recently shown the usefulness of simple models of nucleon separation energies in terms of neutron and proton numbers. However, the customary use of least squares in the process of parameter estimation turns out to be extremely sensible to the accuracy of the model and the extent and quality of data (e.g. highly vulnerable to the sample size or the possible existence of undesired errors in the experimental values). We will show how robust estimation by global optimization instead of least squares estimation improves on both the stability of the estimated parameters and the extrapolation to unknown energies. Comparison against recently determined experimental data will show a level of agreement comparable to the predictions made by the best and much more complex models.

scholarly journals The impact of external financing on firm value and a corporate governance index: SME evidence

2017 ◽  
Vol 24 (2) ◽  
pp. 411-423 ◽  
Author(s):  
Basil Al-Najjar ◽  
Dana Al-Najjar
Keyword(s):  
Corporate Governance ◽  
Least Squares ◽  
Firm Value ◽  
Estimation Methods ◽  
External Financing ◽  
Governance Mechanisms ◽  
Content Type ◽  
Corporate Governance Mechanisms ◽  
Governance Index ◽  
The Impact

Purpose The purpose of this paper is to investigate the effect of external financing needs on both firm value and corporate governance mechanisms within the UK SME context. This framework is of importance because of the limited external financial resources SMEs might face. Design/methodology/approach The authors consider the endogeneity problem between corporate governance mechanisms and firm value, and hence, the three stages least squares and the instrumental variables based on two stages least squares estimation methods are employed. Findings The authors find a positive relationship between external financing needs and firm value. In addition, the authors detect that size and profitability are positively associated with firm value in the sample. Concerning the corporate governance index (CGI), the authors detect that big SMEs and those with low-debt levels have better corporate governance structures. Originality/value The authors employ a CGI for the sample which is constructed using ten corporate governance variables. The authors also examine different factors that affect SMEs 2019 governance by applying different models including logistic analysis.

scholarly journals Added-variable plots for panel-data estimation

2020 ◽  
Vol 20 (1) ◽  
pp. 30-50
Author(s):  
John Luke Gallup
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Regression Line ◽  
Estimation Methods ◽  
Panel Data Estimation ◽  
Regression Parameters ◽  
Added Variable Plots ◽  
Relationship Of ◽  
The Impact ◽  
Data Estimation

In this article, I extend the theory of added-variable plots to three panel-data estimation methods: fixed effects, between effects, and random effects. An added-variable plot is an effective way to show the correlation between an independent variable and a dependent variable conditional on other independent variables. In a multivariate context, a simple scatterplot showing x versus y is not adequate to show the relationship of x with y, because it ignores the impact of the other covariates. Added-variable plots are also useful for spotting influential outliers in the data that affect the estimated regression parameters. Stata can display added-variable plots with the command avplot, but it can be used only after regress. My new command, xtavplot, is a postestimation command that creates added-variable plots after xtreg estimates. Unlike avplot, xtavplot can display a confidence interval around the fitted regression line.

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