Correlation tests for high-dimensional data using extended cross-data-matrix methodology

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Some Tests concerning the Covariance Matrix in High Dimensional Data

In this paper, tests are developed for testing certain hypotheses on the covariance matrix Σ, when the sample size N = n+1 is smaller than the dimension p of the data. Under the condition that (trΣ/p) exists and > 0, as p → ∞, i = 1, . . . , 8, tests are developed for testing the hypotheses that the covariance matrix in a normally distributed data is an identity matrix, a constant time the iden...

متن کامل

Methods for regression analysis in high-dimensional data

By evolving science, knowledge and technology, new and precise methods for measuring, collecting and recording information have been innovated, which have resulted in the appearance and development of high-dimensional data. The high-dimensional data set, i.e., a data set in which the number of explanatory variables is much larger than the number of observations, cannot be easily analyzed by ...

متن کامل

Identity tests for high dimensional data using RMT

In this work, we redefined two important statistics, the CLRT test (Bai et.al., Ann. Stat. 37 (2009) 3822-3840) and the LW test (Ledoit and Wolf, Ann. Stat. 30 (2002) 1081-1102) on identity tests for high dimensional data using random matrix theories. Compared with existing CLRT and LW tests, the new tests can accommodate data which has unknown means and nonGaussian distributions. Simulations d...

متن کامل

Feature Selection for Small Sample Sets with High Dimensional Data Using Heuristic Hybrid Approach

Feature selection can significantly be decisive when analyzing high dimensional data, especially with a small number of samples. Feature extraction methods do not have decent performance in these conditions. With small sample sets and high dimensional data, exploring a large search space and learning from insufficient samples becomes extremely hard. As a result, neural networks and clustering a...

متن کامل

Correlation Visualization of High Dimensional Data Using Topographic Maps

Correlation analysis has always been a key technique for understanding data. However, traditional methods are only applicable on the whole data set, providing only global information on correlations. Correlations usually have a local nature and two variables can be directly and inversely correlated at different points in the same data set. This situation arises typically in nonlinear processes....

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Multivariate Analysis

سال: 2013

ISSN: 0047-259X

DOI: 10.1016/j.jmva.2013.03.007