Description Usage Arguments Details Value Author(s) References See Also
Give a list of estimated kernel matrices and their weights using simple averaging.
1 | ensemble_avg(n, kern_size, beta, error_mat, A_hat)
|
n |
(integer) A numeric number specifying the number of observations. |
kern_size |
(integer, =K) A numeric number specifying the number of kernels in the kernel library. |
beta |
(numeric/character) A numeric value specifying the parameter when
strategy = "exp" |
error_mat |
(matrix, n*K) A n\*kern_size matrix indicating errors. |
A_hat |
(list of length K) A list of projection matrices for every kernels in the kernel library. |
Simple Averaging
Motivated by existing literature in omnibus kernel, we propose another way to obtain the ensemble matrix by simply choosing unsupervised weights u_d=1/D for d=1,2,...D.
A_est |
(matrix, n*n) A list of estimated kernel matrices. |
u_hat |
(vector of length K) A vector of weights of the kernels in the library. |
Wenying Deng
Jeremiah Zhe Liu and Brent Coull. Robust Hypothesis Test for Nonlinear Effect with Gaus- sian Processes. October 2017.
Xiang Zhan, Anna Plantinga, Ni Zhao, and Michael C. Wu. A fast small-sample kernel inde- pendence test for microbiome community-level association analysis. December 2017.
Arnak S. Dalalyan and Alexandre B. Tsybakov. Aggregation by Exponential Weighting and Sharp Oracle Inequalities. In Learning Theory, Lecture Notes in Computer Science, pages 97– 111. Springer, Berlin, Heidelberg, June 2007.
mode: tuning
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