standard error propagation/ A0260 Numerical approximation and analysis A0250 Probability theory, stochastic processes, and statisticsA general method of error estimation in the case of multiple point dimensionl
Consider the linear regression model Y = X+ where Y denotes a vector of n observations on the dependent variable, X is a known matrix, is a vector of parameters to be estimated and e is a random vector of uncorrelated errors. If X''X is nearly singular, that is if the smallest ...
In a regression with independent and identically distributed normal residuals, the log-likelihood function yields an empirical form of the $$\mathcal{L}^2$
where the “latent” explanatory variableξ is not directly observed (hence the Greek letter); x2 is directly observed and measured without error; and the regression error ɛ behaves according to the usual assumptions—in particular, E(ɛi) = 0, and the errors are uncorrelated with each ...
Communications in Statistics Theory & MethodsKubokawa, T. and Erdembat, N. (2011). On testing linear hypothesis in a nested error regression model. Communications in Statistics-Theory and Methods, 39, 1552- 1562.On Testing Linear Hypothesis in a Nested Error Regression Model. Tatsuya Kubokawa,...
(2000). Contingency Theory and Moderated regression Analysis: The Effect of Measurement Level, Measurement Error and Non-Linear Relation. Serie Research Memoranda, Vol: 25 (2), pp.1-21... M Gelderman - 《Research Memoranda》 被引量: 1发表: 2000年 In Pursuit of Moderation: Nine Common Erro...
We average the performance of nine different distance-3 subgrids and four different distance-5 subgrids to compare with the distance-7 code. Finally, we compute Λ using linear regression of ln[εd] versus d. With our neural network decoder, we observe Λ = 2.14 ± 0.02 and ...
Error analysis may thus help to shed light on potential causes of patients’ difficulties in inferring communicative intentions and to evaluate the relationship between these deficits and specific clinical features of the disorder. Signal detection theory (SDT) is a framework used to model performance ...
Volumetric error prediction and compensation models are realized by the forward and inverse kinematics modeling via the screw theory. Key geometric error items of motion axes and their influences on gear tooth performance are modeled and analyzed. Advantages of the proposed compensation method for ...
Albertini and de Mello [226] propose a network that integrates features from SOM, GWR, and adaptive resonance theory networks. When an input is presented, the network searches through categories stored for a match. If no match is found, then the input is considered to be novel. A ligand-ba...