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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...
Selection of variables and dimension reduction in high-dimensional non-parametric regression
dimension reduction high dimension LASSO
2009/9/16
We consider a $l_1$-penalization procedure in the non-parametric Gaussian regression model. In many concrete examples, the dimension $d$ of the input variable $X$ is very large (sometimes depending on...
Theoretical properties of Cook's PFC dimension reduction algorithm for linear regression
Principal Components Principal Fitted Components random matrix theory regression
2009/9/16
We analyse the properties of the Principal Fitted Components (PFC) algorithm proposed by Cook. We derive theoretical properties of the resulting estimators, including sufficient conditions under which...
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...