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In macroeconomic forecasting, principal component analysis (PCA) has been the most prevalent approach to the recovery of factors, which summarize information in a large set of macro predictors. Nevert...
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors,a linear combination of some la...
The traditional variable selection methods for survival data depend on iteration procedures, and control of this process assumes tuning parameters that are problematic and time consuming, especially i...
We study isomorphism invariant point processes of R^d; whose groups of symmetries are almost surely trivial. We define a 1-ended, locally finite tree factor on the points of the process, that is, a ma...
Let X and Y be Poisson point processes on the real numbers with rates l_1 and l_2 respectively. We show that if l_1 > l_2, then there exists a deterministic map f such that f(X) and Y have the same di...
Bayesian Model Calibration is used to revisit the problem of scaling factor calibration for semi-empirical correction of ab initio calculations. A particular attention is devoted to uncertainty eval...
Suppose several two-valued input-output systems are designed by setting the levels of several controllable factors. For this situation, Taguchi method has proposed to assign the controllable factors...
How predictable is the academic success of individual undergraduate students at an AACSB-accredited business school? As a group, undergraduate business students pose many different intelligence leve...

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