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The study of statistical models with error invariables is a well-developed area of statistical and psychometric inquiry.
The use of these reduced models with error control in reacting flow simulations is demonstrated through an Adaptive Chemistry example.
Theorem 1: Suppose the weak learning algorithm (h in varvec{h}), when called by boosting algorithm, generates hypothetical forecast models with error (varepsilon_{1}, ldots,varepsilon_{T}).
We developed consumer credit scoring models with error back-propagation artificial neural networks and checked their efficiency against models developed with logistic regression.
The n-PLS-DA models after metabolite selection for GC-MS global and LC-MS polar metabolome data resulted in models with error rates of 10.5% and 5.0% respectively, indicating that the GC-MS global model and the LC-MS polar model only misclassified respectively 2 and 1 persons of the total 19.
To ensure the reliability of the results, models with error rate of more than 25% were excluded from further analysis.
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Special attention is paid to models with errors satisfying the law of large numbers.
Econometricians were the first to extensively study models with errors in the variables, and their use in econometrics became widespread Anderson, (1984).
Multiple linear regression models with errors capable of correlation or with unequal variances were fitted using the generalized least squares.
Multiple linear regression models with errors that were correlated or had unequal variances were fitted using the generalized least squares and maximum likelihood estimation.
The first stage modelling process, which used a random parameters logit model with error components, suggested that willingness to pay was higher for increasing the abundance of native bird than for non-bird species.
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