scholarly journals On equivalence problem in linear regression models. I. BLUE of the mean value

1980 ◽  
Vol 25 (6) ◽  
pp. 417-422
Author(s):  
Gejza Wimmer
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Equivalence Problem ◽  
Mean Value ◽  
Linear Regression Models ◽  
The Mean

scholarly journals Hypoalbuminaemia as a marker of trans-capillary leakage in community-acquired bacteraemia patients

2018 ◽  
Vol 146 (5) ◽  
pp. 648-655 ◽  
Author(s):  
K. O. Gradel ◽  
P. J. Vinholt ◽  
B. Magnussen ◽  
C. Pedersen ◽  
T. G. Jensen ◽  
...  
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Albumin Level ◽  
Full Model ◽  
Linear Regression Models ◽  
Capillary Leakage ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
The Mean ◽  
Sudden Decrease

AbstractCommunity-acquired bacteraemia patients (n = 2472), Denmark, 2000–2008. Albumin, C-reactive protein (CRP) and haemoglobin (Hb) measured 2000–2010. We assessed daily mean levels of albumin, CRP and Hb from 30 days before to 30 days after bacteraemia and correlations between albumin vs. CRP and albumin vs. Hb. In linear regression models, we evaluated the contribution of CRP, Hb, chronic and acute variables to the albumin level variations. The mean albumin level (33.6 g/l) was steady before day 1, declined to 29.3 g/l on day 1 with little increase afterward. The mean CRP increased from day −5, peaked on day 1 and declined thereafter. The mean Hb level was fairly constant during days −30/30. Albumin was inversely (R range, − 0.18/–0.47, P < 10−4) correlated with the CRP level and positively (R = 0.17–0.46, P < 10−4) correlated with the HB level. In most models, CRP was the first variable that contributed to the albumin variations, 34–70% of the full model. The sudden decrease of albumin levels, without sudden fluctuations of CRP or Hb, indicated that hypoalbuminaemia was a marker of trans-capillary leakage.

Influence of Grip Width and Anthropometric Characteristics on the Bench-Press Load–Velocity Relationship

2020 ◽  
Vol 15 (7) ◽  
pp. 949-957
Author(s):  
Alejandro Pérez-Castilla ◽  
Daniel Jerez-Mayorga ◽  
Dario Martínez-García ◽  
Ángela Rodríguez-Perea ◽  
Luis J. Chirosa-Ríos ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Bench Press ◽  
Linear Regression Models ◽  
Mean Velocity ◽  
Movement Velocity ◽  
Anthropometric Characteristics ◽  
The Mean ◽  
The Individual

Purpose: To compare the load–velocity (L-V) relationship between bench-press exercises performed using 4 different grip widths, to determine the association between the anthropometric characteristics and L-V profile, and to explore whether a multiple linear-regression model with movement velocity and subjects’ anthropometric characteristics as predictor variables could increase the goodness of fit of the individualized L-V relationship. Methods: The individual L-V relationship of 20 men was evaluated by means of an incremental loading test during the bench-press exercise performed on a Smith machine using narrow, medium, wide, and self-selected grip widths. Simple and multiple linear-regression models were performed. Results: The mean velocity associated with each relative load did not differ among the 4 grip widths (P ≥ .130). Only body height and total arm length were correlated with the mean velocity associated with light and medium loads (r ≥ .464). A slightly higher variance of the velocity attained at each relative load was explained when some anthropometric characteristics were used as predictor variables along with the movement velocity (r2 = .969 [.965–.973]) in comparison with the movement velocity alone (r2 = .966 [.955–.968]). However, the amount of variance explained by the individual L-V relationships was always higher than with the multiple linear-regression models (r2 = .995 [.985–1.000]). Conclusions: These results indicate that the individual determination of the L-V relationship using a self-selected grip width could be recommended to monitor relative loads in the Smith machine bench-press exercise.

scholarly journals A Fuzzy-Statistical Tolerance Interval from Residuals of Crisp Linear Regression Models

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1422
Author(s):  
Maryam Al-Kandari ◽  
Kingsley Adjenughwure ◽  
Kyriakos Papadopoulos
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Fuzzy Number ◽  
Regression Models ◽  
Tolerance Interval ◽  
Linear Regression Models ◽  
Fuzzy Linear Regression ◽  
The Mean ◽  
Statistical Tolerance

Linear regression is a simple but powerful tool for prediction. However, it still suffers from some deficiencies, which are related to the assumptions made when using a model like normality of residuals, uncorrelated errors, where the mean of residuals should be zero. Sometimes these assumptions are violated or partially violated, thereby leading to uncertainties or unreliability in the predictions. This paper introduces a new method to account for uncertainty in the residuals of a linear regression model. First, the error in the estimation of the dependent variable is calculated and transformed to a fuzzy number, and this fuzzy error is then added to the original crisp prediction, thereby resulting in a fuzzy prediction. The results are compared to a fuzzy linear regression with crisp input and fuzzy output, in terms of their ability to represent uncertainty in prediction.

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

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.

Sign in / Sign up

Export Citation Format

Share Document