scholarly journals Using Least squares methods and nonlinear regression Methods to Calculate the Approximate Value of Ionicity in Terms of the Energy Gap

2019 ◽  
Vol 24 (5) ◽  
pp. 97
Author(s):  
Ghassan E. Arif ◽  
Sura Y. Jaafar ◽  
, Shymaa M. Abdullah
Keyword(s):  
Regression Analysis ◽  
Numerical Analysis ◽  
Least Squares ◽  
Energy Gap ◽  
Least Squares Method ◽  
Regression Method ◽  
Quadratic Regression ◽  
Nonlinear Method ◽  
Regression Methods ◽  
Analysis Methods

The objective of the current study is to find the best mathematical models to calculate the estimated value of the ionization for the physical compounds of semiconductors based on the energy gap throughout using some numerical analysis methods as the least squares method. The best of its branches obtained is a nonlinear method of the second degree, we compare the new result with other methods and we obtained our new method is more accurate and efficiency. Another side we using some regression analysis methods as the regression method. The best of its branches obtained is a nonlinear method of the quadratic regression model.   http://dx.doi.org/10.25130/tjps.24.2019.097

A Fuzzy Linear Regression Analysis for Fuzzy Input-Output Data Using the Least Squares Method under Linear Constraints and Its Application to Fuzzy Rating Data

1999 ◽  
Vol 3 (1) ◽  
pp. 36-41 ◽  
Author(s):  
Kazuhisa Takemura ◽  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Least Squares ◽  
Least Squares Method ◽  
Linear Regression Analysis ◽  
Linear Constraints ◽  
Fuzzy Linear Regression ◽  
Output Data ◽  
Rating Data ◽  
Fuzzy Input

Fuzzy linear regression analysis using the least squares method under linear constraint, where input data, output data, and coefficients are represented by triangular fuzzy numbers, was proposed and compared to possibilistic linear regression analysis proposed by Sakawa and Yano (1992) using fuzzy rating data in a psychological study. Major findings of the comparison were as follows: (1) Under the proposed analysis, the width between the maximum and minimum of the predicted model was nearer to the width of the dependent variable than that of possibilistic linear regression analysis, (2) the representative prediction by the proposed analysis was also nearer to that of the dependent variable, compared to that of possibilistic linear regression analysis.

scholarly journals Ownership structure and bank performance

2018 ◽  
Vol 13 (1) ◽  
pp. 80-87
Author(s):  
Hamdi Agustin ◽  
Sri Indrastuti ◽  
Amris Rusli Tanjung ◽  
Muhammad Said
Keyword(s):  
Community Development ◽  
Least Squares ◽  
Ownership Structure ◽  
Least Squares Method ◽  
Regression Method ◽  
Bank Performance ◽  
Least Squares Regression ◽  
Private Banks ◽  
Static Effect ◽  
Special Knowledge

The purpose of this study is to evaluate the performance of banks in Indonesia. Specifically, this study has examined the static effect of ownership structure on bank performance in Indonesia over the period 1995–2006. The sample consists of 74 banks, namely 56 private banks, 15 community development banks (BPD), and three federal banks from 1995 to 2006. The data was analyzed using least-squares regression method, the general least squares method, and the method of random effects. The findings of this study show that the BPD performed better compared to private banks. This indicates that BPDs have better performance rather than private banks which is due to the fact that customers can be able to pay loans, they have special knowledge on that area and the performance of BPD is supervised by local government. In addition, the amount of equity, economic growth, financial crisis, and the financial ratios affect the performance of the bank. However, bank status has no effect on bank performance.

scholarly journals Analysis of Efficiency of Least Trimmed Square and Least Median Square Methods in The Estimation of Robust Regression Parameters

2020 ◽  
Vol 4 (1) ◽  
pp. 21
Author(s):  
Hamdan Abdi ◽  
Sajaratud Dur ◽  
Rina Widyasar ◽  
Ismail Husein
Keyword(s):  
Observational Data ◽  
Palm Oil ◽  
Regression Models ◽  
Robust Regression ◽  
Least Squares Method ◽  
Regression Method ◽  
Estimation Methods ◽  
Land Area ◽  
Regression Methods ◽  
Regression Parameters

<span lang="EN">Robust regression is a regression method used when the remainder's distribution is not reasonable, or there is an outreach to observational data that affects the model. One method for estimating regression parameters is the Least Squares Method (MKT). The method is easily affected by the presence of outliers. Therefore we need an alternative method that is robust to the presence of outliers, namely robust regression. Methods for estimating robust regression parameters include Least Trimmed Square (LTS) and Least Median Square (LMS). These methods are estimators with high breakdown points for outlier observational data and have more efficient algorithms than other estimation methods. This study aims to compare the regression models formed from the LTS and LMS methods, determine the efficiency of the model formed, and determine the factors that influence the production of community oil palm in Langkat District in 2018. The results showed that in testing, the estimated model of the regression parameters showed the same results. Compared to the efficiency estimator and the error square value, it was concluded that the LTS method was more efficient. Variable land area and productivity influence the production of palm oil smallholders in Langkat District in 2018. as well as the comparison of the efficiency estimator and the error square value, it was concluded that the LTS method was more efficient. Variable land area and productivity are factors that influence the production of palm oil smallholders in Langkat District in 2018. as well as the comparison of the efficiency estimator and the error square value, it was concluded that the LTS method was more efficient. Variable land area and productivity are factors that influence the production of palm oil smallholders in Langkat District in 2018</span>

scholarly journals A Comparison of OLS and Ridge Regression Methods in the Presence of Multicollinearity Problem in the Data

2018 ◽  
Vol 7 (4.30) ◽  
pp. 36
Author(s):  
N S M Shariff ◽  
H M B Duzan
Keyword(s):  
Regression Analysis ◽  
Least Squares ◽  
Ridge Regression ◽  
Regression Modeling ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Ridge Estimator ◽  
Common Procedure ◽  
Monte Carlo Simulation Study ◽  
Regression Methods

The presence of multicollinearity will significantly lead to inconsistent parameter estimates in regression modeling. The common procedure in regression analysis that is Ordinarily Least Squares (OLS) is not robust to multicollinearity problem and will result in inaccurate model. To solve this problem, a number of methods are developed in the literatures and the most common method is ridge regression. Although there are many studies propose variety method to overcome multicolinearity problem in regression analysis, this study proposes the simplest model of ridge regression which is based on linear combinations of the coefficient of the least squares regression of independent variables to determine the value of  k (ridge estimator in ridge regression model). The performance of the proposed method is investigated and compared to OLS and some recent existing methods. Thus, simulation studies based on Monte Carlo simulation study are considered. The result of this study is able to produce similar findings as in existing method and outperform OLS in the existence of multicollinearity in the regression modeling.

scholarly journals The study of pituitary-thyroid hormones ratio based on regression analysis

2015 ◽  
Vol 96 (5) ◽  
pp. 831-837
Author(s):  
F Kh Kamilov ◽  
V N Kozlov ◽  
V N Baymatov ◽  
A N Mamtsev ◽  
D Yu Smirnov
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Thyroid Hormones ◽  
Least Squares ◽  
Least Squares Method ◽  
Thyroid Stimulating Hormone ◽  
Hormone Levels ◽  
Relationship Of ◽  
The Relationship ◽  
Stimulating Hormone

Aim. To work up a mathematical model for calculation of the levels of pituitary-thyroid hormones system by least squares method in rats with experimental hypothyroidism. Methods. To study the relationship of hormones levels regression analysis was used. The search of coefficients was performed using the least squares method. Investigations were carried out on rats, which were divided into six groups of 12 rats each: the first group was control, in the animals of second, third, fourth, fifth and sixth groups hypothyroidism was induced by daily intragastric administration of tiamazol in following doses: 2.5; 20.0; 10.0; 5.0 and 1.0 mg per 100 g of rat body weight for 3 weeks. Results. Regression analysis was carried out, the type of regression as well as parameters were chosen; statistical analysis of the relationship of hormones was conducted based on the obtained results. By comparing the calculation results of the laboratory analysis sufficiently high reliability of the developed model was set up. The deviation of the arithmetic mean value of the level of thyroid stimulating hormone, produced on the basis of experimental and calculated data, is 2.7%. The accuracy of thyroid stimulating hormone levels calculations increased with the decrease of thyrostatic medication dose. The relative error while calculating the free thyroxine levels in the same groups of rats did not exceed 2.15%, accounting for 1.64; 1.34; 0.36 and 2.15%, respectively, when administered daily 20.0; 10.0; 5.0 and 1.0 mg of antithyroid drug per 100 g body weight. One can argue about the reliability of the constructed model to reproduce the performance levels of the hormones of the pituitary-thyroid system. Conclusion. In the absence of modern high sensitive immunochemiluminescent diagnostic methods the results can be used for thyroid-stimulating hormone levels calculation as one of the major markers of the thyroid gland functional state.

scholarly journals Geodetic Rotation of the Solar System Bodies

2007 ◽  
Vol 42 (1) ◽  
pp. 59-70 ◽  
Author(s):  
G. Eroshkin ◽  
V. Pashkevich
Keyword(s):  
Spectral Analysis ◽  
Solar System ◽  
Angular Velocity ◽  
Least Squares ◽  
Least Squares Method ◽  
Time Span ◽  
The Sun ◽  
The Moon ◽  
Analysis Methods ◽  
Solar System Bodies

Geodetic Rotation of the Solar System Bodies The problem of the geodetic (relativistic) rotation of the major planets, the Moon, and the Sun is studied by using DE404/LE404 ephemeris. For each body the files of the ecliptical components of the vectors of the angular velocity of the geodetic rotation are determined over the time span from AD1000 to AD3000 with one day spacing. The most essential terms of the geodetic rotation are found by means of the least squares method and spectral analysis methods.

scholarly journals Wind Tunnel Results for a Distributed Flush Airdata System

2017 ◽  
Vol 34 (7) ◽  
pp. 1519-1528 ◽  
Author(s):  
Roger J. Laurence ◽  
Brian M. Argrow ◽  
Eric W. Frew
Keyword(s):  
Wind Tunnel ◽  
Least Squares ◽  
Static Pressure ◽  
Least Squares Method ◽  
Angle Of Attack ◽  
Pressure Sensors ◽  
Nonlinear Least Squares ◽  
Unmanned Aircraft ◽  
Regression Methods ◽  
Relative Wind

AbstractThe multihole probe (MHP) is an effective instrument for relative wind measurements from small unmanned aircraft systems (sUAS). Two common drawbacks for the integration of commercial MHP systems into low-cost sUAS are that 1) the MHP airdata system cost can be several times that of the sUAS airframe; and 2) when extended from the airframe, the pressure-measuring probe is often exposed to damage during normal operations. A flush airdata system (FADS) with static pressure sensing ports mounted flush with the airframe skin provides an alternative to the MHP system. This project implements a FADS with multiple static pressure sensors located at selected locations on the airframe. Computational fluid dynamics simulations are used to determine the airframe locations with the highest pressure change sensitivity to changes in the airframe angle of attack and sideslip angle. Wind tunnel test results are reported with nonlinear least squares and neural networks regression methods applied to the pressure measurements to estimate the instantaneous angle of attack and sideslip. Both methods achieved mean errors of less than . A direct comparison of the regression methods show that the neural network method provides a more accurate relative wind angle estimate than the nonlinear least squares method.

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