Effective number of degrees of freedom associated with regression models

2022 ◽  
pp. 23-44
Author(s):  
Alistair B. Forbes
Robotica ◽  
1997 ◽  
Vol 15 (5) ◽  
pp. 563-571 ◽  
Author(s):  
Fernando Reyes ◽  
Rafael Kelly

This paper describes the experimental evaluation of three identification schemes to determine the dynamic parameters of a two degrees of freedom direct-drive robot. These schemes involve a recursive estimator while the regression models are formulated in continuous time. The fact that the total energy of robot manipulators can be represented as a linear relation in the inertial parameters, has motivated the suggestion in the literature of several regression models which are linear in a common dynamic parameter vector. Among them, in this paper we consider the schemes based on the filtered dynamic regression model, the supplied energy regression model and a new one proposed in this paper: the filtered power regression model. The underling recursive parameter estimator used in the experimental evaluation is the standard least-squares.


2020 ◽  
Vol 8 (2) ◽  
pp. 161-175
Author(s):  
N. A. Halushko ◽  
T. O. Tretska ◽  
A. V. Halushko

Introduction/objective. The significant part of young people in the structure of hepatitis C virus (HC/HCV infection) incidence, a lot of latent cases of this infection, and the lack of specific prevention may complicate the epidemic situation regarding this infection in Ukraine in the coming years. The authors developed a mathematical model of the HC epidemiological process to determine the most significant factors in this infection transmission in the country. Materials and methods. The study is based on correlation-regression analysis of the relationship between a dependent (or responding) and explanatory (factorial or predictors) variables. In total, the analysis involved 3 dependent variables y1, y2, y3, corresponding to the annual number of acute and chronic HC cases and the number of HC virus seropositive individuals, and 17 predictors x1 – x17, including patients who received etiotropic treatment; patients with mental and behavioral disorders due to narcotics use, including opioids; patients with sexually transmitted infections; the number of visits to dentists; the number of patients who had dentures placed; the number of surgical operations, blood transfusions, endoscopic examinations, laboratory blood tests, hemodialysis, etc. The number of observations (n) of dependent and explanatory variables was equal to 25, which corresponds to the number of administrative-territorial units in Ukraine (24 regions and Kyiv). The quality of regression models was evaluated using multiple correlation coefficients (R), determination coefficients (R2), and regression coefficients (b0, b1, b2). Statistical significance of R2 was determined by F-statistics, regression coefficients – by standard errors (m), t-test, p-value, and the range of 95% confidence intervals (CI). To compare the degree of influence of factor variables over dependent variables in the two-factor regression model, standardized regression coefficients were calculated. The reliability of regression models was evaluated by the statistics of Durbin–Watson (DW), Breusch–Godfrey (BG), and White (W) tests. The relative risk (RR) of HC infection was retrospectively determined in individuals from behavioral and medical risk groups. Results. In mathematical model of the epidemic process of acute HC, statistical significance was demonstrated for only one variable effect – annual number of dentist visits. The obtained regression equation was as follows: y1 = 0.000021 x5 – 11.353, where y1 = annual number of patients with acute HC; х5 = annual number of dentist visits. Statistical characteristics of the model: R = 0.892, R2 = 0.796; F-test: 89.9 for 1 and 23 degrees of freedom, statistical significance for F: 0.0000000021; regression coefficients: b1= 0.000021 (m = ±0.0000023; t = 9.48, tcrit = 1.71; p = 0.0000000021; 95% CІ [0.000017; 0.000026]), b0 = -11.353 (m = ±3.982; t = 2.85, tcrit = 1.71; p = 0.009; 95% CІ [-19.59; -3.116]). When developing a model of the epidemic process of acute HC taking into account the annual number of seropositive individuals, statistical significance was demonstrated only for two variables: annual number of the sexually transmitted infections and annual number of laboratory blood tests. The analytical relationship of variables in this model had the following mathematical expression: y3 = 4.563 x4 + 0.0058 x15 – 36552.721, where y3 = number of HCV-seropositive individuals; x4 = number of sexually transmitted diseases, x15 = number of laboratory blood tests. Statistical characteristics of the model: R = 0.92, R2 = 0.842; F-test: 58.62 for 2 and 22 degrees of freedom, statistical significance for F: 0.00000000153; regression coefficients: b0= -36552.721 (m = ±10649.1; t = 3.43, tcrit = 1.71; p = 0.0024; 95% CІ [-58637.63; -14467.81]), b1 = 0.0058; m = ±0.00082; t = 7.1, tcrit = 1.71; р = 0.0000004; 95% CІ [0.0041; 0.0075]; b2 = 4.563; m = ±1.526; t = 2.99, tcrit = 1.71; р = 0.0067; 95% CІ [1.4; 7.73]. The Durbin–Watson and Breusch–Godfrey tests did not reveal autocorrelation of residues for both regression models: DWU < DWр < 4 – DWU; BG < χ2. White's test shows no heteroscedasticity for both models: W < χ2. The test results indicate the reliability of both regression models. Conclusions. According to our data, at least 84% of HC virus infection cases in Ukraine occur through sexual contact and during laboratory blood sampling, and the role of the latter route of transmission in the HC virus spread was even more significant (standardized regression coefficients are 0.3 and 0.7, respectively). Almost 80% of acute HC cases are associated with dental interventions. Etiotropic treatment of patients with HC at the current level of treatment coverage can reduce the incidence of complications and the risk of death, but it is ineffective as a measure of influence on the first stage of the epidemiological process (source of infection). Drug users have little effect on the intensity of the HC epidemiological process in Ukraine as a whole, despite the fact that the relative risk of HC among this population is quite significant (RR = 6.5; 95% CI [6.39; 6.63]).


2004 ◽  
Vol 19 (26) ◽  
pp. 4431-4453 ◽  
Author(s):  
A. CUOCO ◽  
F. IOCCO ◽  
G. MANGANO ◽  
G. MIELE ◽  
O. PISANTI ◽  
...  

We report on the status of primordial nucleosynthesis in light of recent results on CMB anisotropies from WMAP experiment. Theoretical estimates for nuclei abundances, along with the corresponding uncertainties, are evaluated using a new numerical code, where all nuclear rates usually considered have been updated using the most recent available data. Moreover, additional processes neglected in previous calculations have been included. The combined analysis of CMB and primordial nucleosynthesis prediction for Deuterium gives an effective number of relativistic degrees of freedom in good agreement with the simplest scenario of three nondegenerate neutrinos. Our findings seem to point out possible systematics affecting 4 He mass fraction measurements, or the effect of exotic physics, like a slightly degenerate relic neutrino background.


1996 ◽  
Vol 21 (4) ◽  
pp. 390-404 ◽  
Author(s):  
Bradley E. Huitema ◽  
Joseph W. McKean ◽  
Jinsheng Zhao

The runs test is frequently recommended as a method of testing for nonindependent errors in time-series regression models. A Monte Carlo investigation was carried out to evaluate the empirical properties of this test using (a) several intervention and nonintervention regression models, (b) sample sizes ranging from 12 to 100, (c) three levels of α, (d) directional and nondirectional tests, and (e) 19 levels of autocorrelation among the errors. The results indicate that the runs test yields markedly asymmetrical error rates in the two tails and that neither directional nor nondirectional tests are satisfactory with respect to Type I error, even when the ratio of degrees of freedom to sample size is as high as .98. It is recommended that the test generally not be employed in evaluating the independence of the errors in time-series regression models.


Author(s):  
Igor Zakharov ◽  
Pavel Neyezhmakov ◽  
Olesia Botsiura

An expression for estimating the combined standard uncertainty taking into account the observed correlation between the estimates of the two input quantities is given. The Welch – Satterthwaite formula given in the GUM is analyzed. It is shown that the number of degrees of freedom calculated using this formula will vary over a wide range when the value of the correlation coefficient changes, and in some cases it may take an unacceptable zero value. An expression for calculating the combined standard uncertainty by the reduction method is given. It is shown that the number of degrees of freedom in this method does not depend on the value of the correlation coefficient. A formula for calculating the effective number of degrees of freedom taking into account the observed correlation is proposed. The existing expression for calculating the kurtosis of the measurand is analyzed and an expression is proposed for calculating the kurtosis of the measurand in the presence of a correlation between the input quantities. An example of estimation of expanded uncertainty when measuring the coefficient of a pressure transducer using a calibrator is considered. Estimates of the distribution of the measurand, obtained using Monte Carlo simulation, showed that they are closest to the estimates obtained by the kurtosis method. The considered example showed that taking into account the correlation in the processing of measurement results makes it possible to reduce the expanded measurement uncertainty of the converter coefficient by 1.22–1.27 times. Keywords: measurement uncertainty; correlation; effective number of degrees of freedom; method of kurtosis


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