While interpretingthe coefficientof one of the predictors (saya continuous variable X1) of a linear model — with multiple explanatory variables (X1, X2, …..Xn) predicting the value of an outcome variable (Y) — you must have used statements such as the following: “Controlling for ot...
In this paper, the issue of other possible regression adjustments is discussed. In particular, a regression of each variable for those driving it is considered. It is shown under what circumstances this adjustment is appropriate, and its diagnostic power is illustrated by examples....
aremaining factor 剩余的因素[translate] aDemographic variablesc were also entered into the regression model to control for their relationships with the dependent variable 人口统计的variableswere也加入回归模型为他们的与因变量的关系控制[translate]
Regression analyses using ANS-IE scores as the predictor variable supported the hypotheses. Compared to women with internal orientations, subjects with external orientations expected to have less commitment to their careers, to work for a smaller portion of their lives, and to feel more discomfort ...
R2 values represent model fit and are important indicators of the goodness of fit of a linear equation, reflecting the ability of the regression model to explain the variation of the dependent variable. In this model, R2 was 0.6641, indicating the goodness of fit of the model, where 66.41% ...
Computed Torque Control with Variable Gains through Gaussian Process Regression 来自 掌桥科研 喜欢 0 阅读量: 27 作者:NT Alberto,M Mistry,F Stulp 摘要: In computed torque control, robot dynamics are predicted by dynamic models. This enables more compliant control, as the gains of the feedback ...
For regression-based control design of the second kind, machine learning is exploited to identify arbitrary nonlinear control laws that minimize the cost function of the system. In this case, it is not necessary to know the model, control law structure, or the optimizing actuation command, and ...
However, the use of machine learning schemes such as support vector regression, SVM, and artificial neural network (ANN) is well-established in other process monitoring situations. To address this gap in healthcare applications, this paper introduces an SVM-based control chart (SVM-EWMA) to ...
A Confounder is a variable whose presence affects the variables being studied so that the results do not reflect the actual relationship. There are various ways to exclude or control confounding variables including Randomization, Restriction and Matching. But all these methods are applicable at the ti...
An online Gaussian process regression is fed with the joints angles and interaction forces with the thigh cuffs in [59]. In [159], the gait phase is estimated with a decision tree, from the segments IMU data and the feet loads. In [160], deep learning is used on the shank and thigh...