WeiYa's Work Yard

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

Exponential Twisting in Importance Sampling

September 18, 2019

This note is based on Ma, J., Du, K., & Gu, G. (2019). An efficient exponential twisting importance sampling technique for pricing financial derivatives. Communications in Statistics - Theory and Methods, 48(2), 203–219.

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Feature Annealed Independent Rules

September 17, 2019

This note is based on Fan, J., & Fan, Y. (2008). High-dimensional classification using features annealed independence rules. The Annals of Statistics, 36(6), 2605–2637.

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Sparse LDA

September 17, 2019

This note is based on Shao, J., Wang, Y., Deng, X., & Wang, S. (2011). Sparse linear discriminant analysis by thresholding for high dimensional data. The Annals of Statistics, 39(2), 1241–1265.

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Basic of $B$-splines

September 09, 2019 0 Comments

This note is based on de Boor, C. (1978). A Practical Guide to Splines, Springer, New York.

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Likelihood-free inference by ratio estimation

September 09, 2019 0 Comments

This note is for Thomas, O., Dutta, R., Corander, J., Kaski, S., & Gutmann, M. U. (2016). Likelihood-free inference by ratio estimation. ArXiv:1611.10242 [Stat]., and I got this paper from Xi’an’s blog.

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Debiased Lasso

September 08, 2019

This post is based on Section 6.4 of Hastie, Trevor, Robert Tibshirani, and Martin Wainwright. “Statistical Learning withSparsity,” 2016, 362.

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Optimal estimation of functionals of high-dimensional mean and covariance matrix

August 26, 2019

This post is based on Fan, J., Weng, H., & Zhou, Y. (2019). Optimal estimation of functionals of high-dimensional mean and covariance matrix. ArXiv:1908.07460 [Math, Stat].

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Interior-point Method

August 16, 2019

Nocedal and Wright (2006) and Boyd and Vandenberghe (2004) present slightly different introduction on Interior-point method. More specifically, the former one only considers equality constraints, while the latter incorporates the inequality constraints.

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Dantzig Selector

August 16, 2019

This post is based on Candes, E., & Tao, T. (2007). The Dantzig selector: Statistical estimation when $p$ is much larger than $n$. The Annals of Statistics, 35(6), 2313–2351.

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Additive Bayesian Variable Selection

August 05, 2019

This post is based on Rossell, D., & Rubio, F. J. (2019). Additive Bayesian variable selection under censoring and misspecification. ArXiv:1907.13563 [Math, Stat].

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Reluctant Interaction Modeling

July 23, 2019

This note is based on Yu, G., Bien, J., & Tibshirani, R. (2019). Reluctant Interaction Modeling. ArXiv:1907.08414 [Stat].

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The Simplex Method

July 23, 2019

This note is based on Chapter 13 of Nocedal, J., & Wright, S. (2006). Numerical optimization. Springer Science & Business Media.

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An Adaptive Algorithm for online FDR

July 21, 2019

This post is based on Ramdas, A., Zrnic, T., Wainwright, M., & Jordan, M. (2018). SAFFRON: An adaptive algorithm for online control of the false discovery rate. ArXiv:1802.09098 [Cs, Math, Stat].

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High-dimensional linear mixed-effect model

July 21, 2019

This post is based on Li, S., Cai, T. T., & Li, H. (2019). Inference for high-dimensional linear mixed-effects models: A quasi-likelihood approach. ArXiv:1907.06116 [Stat].

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A Optimal Control Approach for Deep Learning

July 19, 2019

This note is based on Li, Q., & Hao, S. (2018). An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks. ArXiv:1803.01299 [Cs].

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Rare Variant Association Testing

July 18, 2019

This note is based on

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Multi-estimate extraction for SMC-PHD

July 17, 2019

This post is based on Li, T., Corchado, J. M., Sun, S., & Fan, H. (2017). Multi-EAP: Extended EAP for multi-estimate extraction for SMC-PHD filter. Chinese Journal of Aeronautics, 30(1), 368–379.

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SMC-PHD Filter

July 17, 2019

This post is based on Ristic, B., Clark, D., & Vo, B. (2010). Improved SMC implementation of the PHD filter. 2010 13th International Conference on Information Fusion, 1–8.

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Canonical Variate Analysis

July 16, 2019

This note is based on Campbell, N. A. (1979). CANONICAL VARIATE ANALYSIS: SOME PRACTICAL ASPECTS. 243.

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High Dimensional LDA

July 15, 2019

This note is for Cai, T. T., & Zhang, L. (n.d.). High dimensional linear discriminant analysis: Optimality, adaptive algorithm and missing data. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 0(0).

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Global data association for MOT using network flows

July 10, 2019

This note is based on Li Zhang, Yuan Li, & Nevatia, R. (2008). Global data association for multi-object tracking using network flows. 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1–8.

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TreeClone

July 08, 2019

This note is based on Zhou, T., Sengupta, S., Müller, P., & Ji, Y. (2019). TreeClone: Reconstruction of tumor subclone phylogeny based on mutation pairs using next generation sequencing data. The Annals of Applied Statistics, 13(2), 874–899.

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MLE for MTP2

July 05, 2019

This post is based on Lauritzen, S., Uhler, C., & Zwiernik, P. (2019). Maximum likelihood estimation in Gaussian models under total positivity. The Annals of Statistics, 47(4), 1835–1863.

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Minimax Lower Bounds

June 28, 2019

This note is based on Chapter 15 of Wainwright, M. (2019). High-Dimensional Statistics: A Non-Asymptotic Viewpoint (Cambridge Series in Statistical and Probabilistic Mathematics). Cambridge: Cambridge University Press.

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Bayesian Conjugate Gradient Method

June 27, 2019

This note is for Cockayne, J., Oates, C. J., Ipsen, I. C. F., & Girolami, M. (2018). A Bayesian Conjugate Gradient Method. Bayesian Analysis.

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Surprises in High-Dimensional Ridgeless Least Squares Interpolation

June 24, 2019

This post is based on Hastie, T., Montanari, A., Rosset, S., & Tibshirani, R. J. (2019). Surprises in High-Dimensional Ridgeless Least Squares Interpolation. 53.

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Medicine Meets AI

June 23, 2019

Last two days, I attended the conference Medicine Meets AI 2019: East Meets West, which help me know more AI from the industrial and medical perspective.

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Change Points

May 28, 2019

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M-estimator

May 09, 2019

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Fourier Series

May 07, 2019

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