Bayesian sen- sitivity analysis in elliptical linear regression models. Journal of Statistical Planning and Inference, (86):175-199, 2000.Arellano-Vallea RB, Galea-Rojasb M, Zuazola PI (2000) Bayesian sensitivit
This volume treats linear regression diagnostics as a tool for the application of linear regression models to real-life data. The presentation makes extensive use of examples to illustrate theory. The text assesses the effect of measurement errors on the estimated coefficients, which is not accounted...
K. (2011). Evaluation of logistic regression and neural network model with sensitivity analysis on medical datasets. International journal of computer science and security, 5, 503-511. http://dx.doi.org/10.1.1.228.884BK R, Srivatsa S. Evaluation of Logistic Regression and Neural Net- work ...
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Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on response variables. In this paper, a new kernel function derived from orthogonal polynomials is proposed for support vector regression (SVR). Based on this new kernel function, the ...
但是sobol函数还需要两组样本，X1和X2，它们是矩阵，其中每行是输入的独立实现。它们应该从输入的联合...
In theStatisticstab of the app, select the evaluation results you want to analyze in theEvaluation Results to Analyzelist. Specify the statistical analysis methods. You can choose to calculate a correlation coefficient, standardized regression coefficient, and partial correlation coefficient (requires Stat...
According to linear regression analysis, no correlation was observed between the VvCYP51 expression levels and tebuconazole sensitivity (Fig. 4). Fitness of mutant/transformants containing the Y137H mutation. Comparison of myce- lial growth rate, sporulation and spore germination showed no ...
We propose global sensitivity analysis using polynomial chaos-based surrogates. • We perform vector projection-based sensitivity analysis for multivariate outputs. • Polynomial chaos-based surrogates are more efficiency than Monte Carlo method. • Proper orthogonal decomposition increases efficiency of ...
with a two-sided Bayesian two-sample t-test finding anecdotal evidence in favour of the null (BF10 = 0.51; variance of normal population: noninformative Jeffreys prior, standardized effect size: Cauchy prior; BF calculated via Gaussian quadrature). Further, we used linear regression on data...