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Topics in Multivariate Time Series Analysis: Statistical Control, Dimension Reduction Visualization and Thir Business Applications
Topics in Multivariate Time Series Analysis Statistical Control Dimension Reduction Visualization Their Business Applications
2014/10/28
Most business processes are, by nature, multivariate and autocorrelated. Highdimensionality is rooted in processes where more than one variable is considered simultaneously to provide a more comprehen...
Dimension reduction in representation of the data
Data representation data analysis data mining
2010/3/18
Suppose the data consist of a set S of points xj , 1 ≤ j ≤ J, distributed in a
bounded domain D RN, where N is a large number. An algorithm is given
for finding the sets Lk of dimension k N, k = 1, ...
Dimension reduction based on constrained canonical correlation and variable filtering
Canonical correlation dimension reduction L1-norm constraint
2010/4/30
The “curse of dimensionality” has remained a challenge for highdimensional
data analysis in statistics. The sliced inverse regression
(SIR) and canonical correlation (CANCOR) methods aim to reduce
...
A new algorithm for estimating the effective dimension-reduction subspace
dimension-reduction multi-index regression model structureadaptive approach central subspace average derivative estimator
2010/4/26
The statistical problem of estimating the effective dimensionreduction
(EDR) subspace in the multi-index regression model with
deterministic design and additive noise is considered. A new procedure
...
A Constructive Approach to the Estimation of Dimension Reduction Directions
Conditional density function Convergence of algorithm Doublekernelsmoothing Efficient dimension reduction Root-n consistency
2010/4/26
In this paper, we propose two new methods to estimate the dimensionreduction
directions of the central subspace (CS) by constructing a regression
model such that the directions are all captured in t...