Order-preserving factor analysis (OPFA)

Details Order-preserving factor analysis (OPFA) Order-preserving factor analysis (OPFA)

2011-05-09

arxiv.org/abs/1105.1758v1

Statistics

Machine Learning

Technical Report - Communications and Signal Processing Laboratory, University of Michigan, Ann Arbor, MI

Scientific paper

We present a novel factor analysis method that can be applied to the discovery of common factors shared among trajectories in multivariate time series data. These factors satisfy a precedence-ordering property: certain factors are recruited only after some other factors are activated. Precedence-ordering arise in applications where variables are activated in a specific order, which is unknown. The proposed method is based on a linear model that accounts for each factor's inherent delays and relative order. We present an algorithm to fit the model in an unsupervised manner using techniques from convex and non-convex optimization that enforce sparsity of the factor scores and consistent precedence-order of the factor loadings. We illustrate the Order-Preserving Factor Analysis (OPFA) method for the problem of extracting precedence-ordered factors from a longitudinal (time course) study of gene expression data.

Affiliated with

Also associated with

No associations

Rating

Order-preserving factor analysis (OPFA) does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Order-preserving factor analysis (OPFA), we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Order-preserving factor analysis (OPFA) will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-334651