Korea University Department of Statistics

2010년 9회 세미나 개최를 알려드리고자 합니다.

일시: 2010년 11월 17일(수) 오후 5시

장소: 고려대학교 정경관 507호

연사: Lee Seok-Ho

(Department of Statistics,

Hankuk University of Foreign Studies)

"Sparse Logistic Principal Components Analysis

for Binary Data"

<Abstract>

We develop a new principal components analysis (PCA) type dimension reduction method for binary data. Different from the standard PCA which is defined on the observed data, the proposed PCA is defined on the logit transform of success probabilities of the binary observations. Sparsity is introduced to the principal component (PC) loading vectors for enhanced interpretability and more stable extraction of the principal components. Our sparse PCA is formulated as solving an optimization problem with a criterion function motivated from penalized Bernoulli likelihood. A Majorization-Minimization algorithm is developed to efficiently solve the optimization problem. The effectiveness of the proposed sparse logistic PCA method is illustrated by application to a single nucleotide polymorphisms data set and a simulation study.