scholarly journals SOFTWARE PACKAGE FOR CONSTRUCTING LINEAR REGRESSION models USING THE MIXED ESTIMATION METHOD

2021 ◽  
pp. 38-42
Author(s):  
С.И. Носков ◽  
К.С. Перфильева
Keyword(s):  
Linear Regression ◽  
Software Package ◽  
Estimation Method ◽  
Rail Transportation ◽  
Linear Regression Models ◽  
Road Transportation ◽  
Approximation Errors ◽  
Behavior Consistency ◽  
Mixed Estimation ◽  
Inland Water Transport

В статье описывается программный комплекс, обеспечивающий возможность оценивания параметров линейного регрессионного уравнения методами смешанного оценивания (МСО), наименьших квадратов (МНК) и модулей (МНМ), а также антиробастного оценивания (МАО). Разработанный программный комплекс применен для моделирования объема погрузки основных видов грузов железнодорожным транспортом, в качестве независимых переменных определены объемы погрузки конкурирующими видами транспорта. Это такие факторы, как перевозки автомобильным, морским, трубопроводным и внутренним водным транспортом. Проведён анализ полученных моделей, оценены значения критериев смещения, относительных ошибок аппроксимации, согласованности поведения. The article considers a software package that provides the ability to estimate the parameters of a linear regression equation using mixed estimation (MSO), least squares (OLS) and modules (MCM), as well as anti-blast estimation (MAO). The developed software package was used to model the volume of loading of the main types of cargo by rail, and the competing types of transportation in relation to rail transportation were selected as independent variables. These are such factors as transportation by road, transportation by sea, transportation by pipeline, transportation by inland water transport. The analysis of the obtained models is carried out, the bias criteria, the relative approximation errors, and the generalized behavior consistency criterion (RSPC) are evaluated.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Linear Regression Models for Interval-Valued Data using Log-transformation

2020 ◽  
Author(s):  
Nykolas Mayko Maia Barbosa ◽  
João Paulo Pordeus Gomes ◽  
César Lincoln Cavalcante Mattos ◽  
Diêgo Farias Oliveira
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Log Transformation ◽  
Interval Valued

Folate Nutritional Status among Psoriasis Patients not Exposed to Antifolate Drug

2020 ◽  
Vol 16 (4) ◽  
pp. 543-553
Author(s):  
Luciana Y. Tomita ◽  
Andréia C. da Costa ◽  
Solange Andreoni ◽  
Luiza K.M. Oyafuso ◽  
Vânia D’Almeida ◽  
...  
Keyword(s):  
Folic Acid ◽  
Linear Regression ◽  
Multiple Linear Regression Model ◽  
Folate Intake ◽  
Serum Folate ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Folic Acid Fortification ◽  
Plasma Folate ◽  
Psoriasis Severity

Background: Folic acid fortification program has been established to prevent tube defects. However, concern has been raised among patients using anti-folate drug, i.e. psoriatic patients, a common, chronic, autoimmune inflammatory skin disease associated with obesity and smoking. Objective: To investigate dietary and circulating folate, vitamin B12 (B12) and homocysteine (hcy) in psoriatic subjects exposed to the national mandatory folic acid fortification program. Methods: Cross-sectional study using the Food Frequency Questionnaire, plasma folate, B12, hcy and psoriasis severity using the Psoriasis Area and Severity Index score. Median, interquartile ranges (IQRs) and linear regression models were conducted to investigate factors associated with plasma folate, B12 and hcy. Results: 82 (73%) mild psoriasis, 18 (16%) moderate and 12 (11%) severe psoriasis. 58% female, 61% non-white, 31% former smokers, and 20% current smokers. Median (IQRs) were 51 (40, 60) years. Only 32% reached the Estimated Average Requirement of folate intake. Folate and B12 deficiencies were observed in 9% and 6% of the blood sample respectively, but hyperhomocysteinaemia in 21%. Severity of psoriasis was negatively correlated with folate and B12 concentrations. In a multiple linear regression model, folate intake contributed positively to 14% of serum folate, and negative predictors were psoriasis severity, smoking habits and saturated fatty acid explaining 29% of circulating folate. Conclusion: Only one third reached dietary intake of folate, but deficiencies of folate and B12 were low. Psoriasis severity was negatively correlated with circulating folate and B12. Stopping smoking and a folate rich diet may be important targets for managing psoriasis.

THE PREDICTIVE CONTENT OF DISAGGREGATED NORMAL INCOME: An Empirical Study in the JSX

2003 ◽  
Vol 5 (3) ◽  
pp. 363 ◽  
Author(s):  
Slamet Sugiri
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Stock Exchange ◽  
Manufacturing Firms ◽  
Single Step ◽  
Model Parameters ◽  
Linear Regression Models ◽  
Operating Income ◽  
Predictive Content ◽  
Multiple Step

The main objective of this study is to examine a hypothesis that the predictive content of normal income disaggregated into operating income and nonoperating income outperforms that of aggregated normal income in predicting future cash flow. To test the hypothesis, linear regression models are developed. The model parameters are estimated based on fifty-five manufacturing firms listed in the Jakarta Stock Exchange (JSX) up to the end of 1997.This study finds that empirical evidence supports the hypothesis. This evidence supports arguments that, in reporting income from continuing operations, multiple-step approach is preferred to single-step one.

Análise da relação entre O3, NO e NO2 usando técnicas de regressão linear múltipla.

GEOgraphia ◽  
2018 ◽  
Vol 20 (43) ◽  
pp. 124
Author(s):  
Amaury De Souza ◽  
Priscilla V Ikefuti ◽  
Ana Paula Garcia ◽  
Debora A.S Santos ◽  
Soetania Oliveira
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Nitrogen Dioxide ◽  
Multiple Linear Regression ◽  
Quality Parameters ◽  
Environmental Pollutant ◽  
Environmental Research ◽  
Linear Regression Models ◽  
Mato Grosso ◽  
The Impact

Análise e previsão de parâmetros de qualidade do ar são tópicos importantes da pesquisa atmosférica e ambiental atual, devido ao impacto causado pela poluição do ar na saúde humana. Este estudo examina a transformação do dióxido de nitrogênio (NO2) em ozônio (O3) no ambiente urbano, usando o diagrama de séries temporais. Foram utilizados dados de concentração de poluentes ambientais e variáveis meteorológicas para prever a concentração de O3 na atmosfera. Foi testado o emprego de modelos de regressão linear múltipla como ferramenta para a predição da concentração de O3. Os resultados indicam que o valor da temperatura e a presença de NO2 influenciam na concentração de O3 em Campo Grande, capital do Estado do Mato Grosso do Sul. Palavras-chave: Ozônio. Dióxido de nitrogênio. Séries cronológicas. Regressões. ANALYSIS OF THE RELATIONSHIP BETWEEN O3, NO AND NO2 USING MULTIPLE LINEAR REGRESSION TECHNIQUES.Abstract: Analysis and prediction of air quality parameters are important topics of current atmospheric and environmental research due to the impact caused by air pollution on human health. This study examines the transformation of nitrogen dioxide (NO2) into ozone (O3) in the urban environment, using the time series diagram. Environmental pollutant concentration and meteorological variables were used to predict the O3 concentration in the atmosphere. The use of multiple linear regression models was tested as a tool to predict O3 concentration. The results indicate that the temperature value and the presence of NO2 influence the O3 concentration in Campo Grande, capital of the State of Mato Grosso do Sul.Keywords: Ozone. Nitrogen dioxide. Time series. Regressions. ANÁLISIS DE LA RELACIÓN ENTRE O3, NO Y NO2 UTILIZANDO MÚLTIPLES TÉCNICAS DE REGRESIÓN LINEAL.Resumen: Análisis y previsión de los parámetros de calidad del aire son temas importantes de la actual investigación de la atmósfera y el medio ambiente, debido al impacto de la contaminación atmosférica sobre la salud humana. Este estudio examina la transformación del dióxido de nitrógeno (NO2) en ozono (O3) en el entorno urbano, utilizando el diagrama de series de tiempo. Las concentraciones de los contaminantes ambientales de datos y variables climáticas fueron utilizadas para predecir la concentración de O3 en la atmósfera. El uso de múltiples modelos de regresión lineal como herramienta para predecir la concentración de O3 se puso a prueba. Los resultados indican que el valor de la temperatura y la presencia de NO2 influyen en la concentración de O3 en Campo Grande, capital del Estado de Mato Grosso do Sul.Palabras clave: Ozono. Dióxido de nitrógeno. Series de tiempo. Regresiones.

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