WeiYa's Work Yard

A dog, who fell into the ocean of statistics, tries to write down his ideas and notes to save himself.

Rademacher Complexity

January 16, 2020

This post is based on the material of the second lecture of STAT 6050 instructed by Prof. Wicker, and mainly refer some more formally description from the book, Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar - Foundations of Machine Learning-The MIT Press (2012).

Continue reading



Classification with Imperfect Training Labels

January 15, 2020

This post is based on the talk, given by Timothy I. Cannings at the 11th ICSA International Conference on Dec. 22th, 2019, the corresponding paper is Cannings, T. I., Fan, Y., & Samworth, R. J. (2019). Classification with imperfect training labels. ArXiv:1805.11505 [Math, Stat]

Continue reading



NGS for NGS

January 11, 2020

This post is based on the talk, Next-Generation Statistical Methods for Association Analysis of Now-Generation Sequencing Studies, given by Dr. Xiang Zhan at the Department of Statistics and Data Science, Southern University of Science and Technology on Jan. 05, 2020.

Continue reading



Concentration Inequality for Machine Learning

January 09, 2020

This post is based on the material of the first lecture of STAT6050 instructed by Prof. Wicker.

Continue reading



DNA copy number profiling: from bulk tissue to single cells

January 02, 2020

This post is based on the talk given by Yuchao Jiang at the 11th ICSA International Conference on Dec. 20th, 2019.

Continue reading



CEASE

December 20, 2019

This post is based on the Peter Hall Lecture given by Prof. Jianqing Fan at the 11th ICSA International Conference on Dec. 20th, 2019.

Continue reading



Group Inference in High Dimensions

December 17, 2019

This post is based on the slides for the talk given by Zijian Guo at The International Statistical Conference In Memory of Professor Sik-Yum Lee

Continue reading



Lagrange Multiplier Test

December 17, 2019

This post is based on Peter BENTLER’s talk, S.-Y. Lee’s Lagrange Multiplier Test in Structural Modeling: Still Useful? in the International Statistical Conference in Memory of Professor Sik-Yum Lee.

Continue reading



Conditional Quantile Regression Forests

December 12, 2019

This note is based on the slides of the seminar, Dr. ZHU, Huichen. Conditional Quantile Random Forest.

Continue reading



Quantile Regression Forests

December 10, 2019

This post is based on Meinshausen, N. (2006). Quantile Regression Forests. 17. since a coming seminar is related to such topic.

Continue reading



Fantastic Generalization Measures and Where to Find Them

December 06, 2019

The post is based on Jiang, Y., Neyshabur, B., Mobahi, H., Krishnan, D., & Bengio, S. (2019). Fantastic Generalization Measures and Where to Find Them. ArXiv:1912.02178 [Cs, Stat].which was shared by one of my friend in the WeChat Moment, and then I took a quick look.

Continue reading



Combining $p$-values in Meta Analysis

December 04, 2019

I came across the term meta-analysis in the previous post, and I had another question about nominal size while reading the paper of the previous post, which reminds me Keith’s notes. By coincidence, I also find the topic about meta-analysis in the same notes. Hence, this post is mainly based on Keith’s notes, and reproduce the power curves by myself.

Continue reading



Controlling bias and inflation in EWAS/TWAS

December 04, 2019

The post is based on the BIOS Consortium, van Iterson, M., van Zwet, E. W., & Heijmans, B. T. (2017). Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution. Genome Biology, 18(1), 19.

Continue reading



Union-intersection tests and Intersection-union tests

December 02, 2019

This post is based on section 8.3 of Casella and Berger (2001).

Continue reading



Gaussian DAGs on Network Data

November 19, 2019

This post is based on Li, H., & Zhou, Q. (2019). Gaussian DAGs on network data. ArXiv:1905.10848 [Cs, Stat].

Continue reading



Active Contours

November 12, 2019

This post is based on Ray, N., & Acton, S. T. (2002). Active contours for cell tracking. Proceedings Fifth IEEE Southwest Symposium on Image Analysis and Interpretation, 274–278.

Continue reading



Multivariate Mediation Effects

November 04, 2019

This note is based on Huang, Y.-T. (2019). Variance component tests of multivariate mediation effects under composite null hypotheses. Biometrics, 0(0).

Continue reading



The Cost of Privacy

November 01, 2019

This note is based on Cai, T. T., Wang, Y., & Zhang, L. (2019). The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy. ArXiv:1902.04495 [Cs, Stat].

Continue reading



MM algorithm for Variance Components Models

November 01, 2019

The post is based on Zhou, H., Hu, L., Zhou, J., & Lange, K. (2019). MM Algorithms for Variance Components Models. Journal of Computational and Graphical Statistics, 28(2), 350–361.

Continue reading



Genetic Relatedness in High-Dimensional Linear Models

October 31, 2019

This post is based on Guo, Z., Wang, W., Cai, T. T., & Li, H. (2019). Optimal Estimation of Genetic Relatedness in High-Dimensional Linear Models. Journal of the American Statistical Association, 114(525), 358–369.

Continue reading



Model-based Approach for Joint Analysis of Single-cell data

October 31, 2019

This post is based on Lin Z†, Zamanighomi M, Daley T, Ma S and Wong WH†: Model-based approach to the joint analysis of single-cell data on chromatin accessibility and gene expression. Statistical Science

Continue reading



Partial Least Squares for Functional Data

October 31, 2019

This post is based on Delaigle, A., & Hall, P. (2012). Methodology and theory for partial least squares applied to functional data. The Annals of Statistics, 40(1), 322–352.

Continue reading



Generalized Functional Linear Models with Semiparametric Single-index Interactions

October 29, 2019

This post is based on Li, Y., Wang, N., & Carroll, R. J. (2010). Generalized Functional Linear Models With Semiparametric Single-Index Interactions. Journal of the American Statistical Association, 105(490), 621–633.

Continue reading



Isotropic vs. Anisotropic

October 24, 2019

I came across isotropic and anisotropic covariance functions in kjytay’s blog, and then I found more materials, chapter 4 from the book Gaussian Processes for Machine Learning, via the reference in StackExchange: What is an isotropic (spherical) covariance matrix?.

Continue reading



Noise Outsourcing

October 10, 2019

I learnt the term Noise Outsourcing in kjytay’s blog, which is based on Teh Yee Whye’s IMS Medallion Lecture at JSM 2019.

Continue reading



Linear Regression with Partially Shuffled Data

October 08, 2019

This post is based on Slawski, M., Diao, G., & Ben-David, E. (2019). A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data. ArXiv:1910.01623 [Cs, Stat].

Continue reading



Sub Gaussian

October 05, 2019

This post is based on Wainwright (2019).

Continue reading



Kernel Ridgeless Regression Can Generalize

September 30, 2019

This note is based on Liang, T., & Rakhlin, A. (2018). Just Interpolate: Kernel “Ridgeless” Regression Can Generalize. ArXiv:1808.00387 [Cs, Math, Stat].

Continue reading



Optimality for Sparse Group Lasso

September 29, 2019

This note is based on Cai, T. T., Zhang, A., & Zhou, Y. (2019). Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference. ArXiv:1909.09851 [Cs, Math, Stat].

Continue reading



ABC for Socks

September 24, 2019 0 Comments

This post is based on Prof. Robert’s slides on JSM 2019 and an intuitive blog from Rasmus Bååth.

Continue reading



See all posts →