WeiYa's Work Yard

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

Stein's Paradox

February 21, 2019

I learned Stein’s Paradox from Larry Wasserman’s post, STEIN’S PARADOX, it seems that I encountered this term before but I cannot recall anything about it. (I am guilty)

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Continuous Time Markov Chain

February 20, 2019

This note is based on Karl Sigman’s IEOR 6711: Continuous-Time Markov Chains.

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Restricted Isometry Property

February 19, 2019

I encounter the term RIP in Larry Wasserman’s post, RIP RIP (Restricted Isometry Property, Rest In Peace), and also find some material in Hastie et al.’s book: Statistical Learning with Sparsity about RIP.

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Presistency

February 18, 2019

The paper, Greenshtein and Ritov (2004), is recommended by Larry Wasserman in his post Consistency, Sparsistency and Presistency.

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A Bayesian Perspective of Deep Learning

February 17, 2019

This note is for Polson, N. G., & Sokolov, V. (2017). Deep Learning: A Bayesian Perspective. Bayesian Analysis, 12(4), 1275–1304.

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Deep Learning

February 16, 2019

This note is based on LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.

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Studentized U-statistic

February 15, 2019 0 Comments

In Prof. Shao’s wonderful talk, Wandering around the Asymptotic Theory, he mentioned the Studentized U-statistics. I am interested in the derivation of the variances in the denominator.

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Review of Composite Likelihood

February 13, 2019

This note is based on Varin, C., Reid, N., & Firth, D. (2011). AN OVERVIEW OF COMPOSITE LIKELIHOOD METHODS. Statistica Sinica, 21(1), 5–42., a survey of recent developments in the theory and application of composite likelihood.

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Gibbs Sampling for the Multivariate Normal

February 13, 2019

This note is based on Chapter 7 of Hoff PD. A first course in Bayesian statistical methods. Springer Science & Business Media; 2009 Jun 2.

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Identification of PE Genes in Cell Cycle

February 13, 2019

This note is based on Fan, X., Pyne, S., & Liu, J. S. (2010). Bayesian meta-analysis for identifying periodically expressed genes in fission yeast cell cycle. The Annals of Applied Statistics, 4(2), 988–1013.

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Comparisons of Three Likelihood Criteria

February 12, 2019

The note is for Nelder, J. A., & Lee, Y. (1992). Likelihood, Quasi-Likelihood and Pseudolikelihood: Some Comparisons. Journal of the Royal Statistical Society. Series B (Methodological), 54(1), 273–284.

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The First Glimpse into Pseudolikelihood

February 12, 2019

This post caught a glimpse of the pseudolikelihood.

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Calculating Marginal likelihood

January 30, 2019

The note is for Fourment, M., Magee, A. F., Whidden, C., Bilge, A., Matsen IV, F. A., & Minin, V. N. (2018). 19 dubious ways to compute the marginal likelihood of a phylogenetic tree topology.

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Annealed Importance Sampling

January 28, 2019

This is the note for Neal, R. M. (1998). Annealed Importance Sampling. ArXiv:Physics/9803008.

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Annealed SMC for Bayesian Phylogenetics

January 24, 2019

This note is for Wang, L., Wang, S., & Bouchard-Côté, A. (2018). An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics. ArXiv:1806.08813 [q-Bio, Stat].

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The Kalman Filter and Extended Kalman Filter

January 21, 2019

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Sequential Monte Carlo Methods

January 19, 2019

This note is for Section 3 of Doucet, A., & Johansen, A. M. (2009). A tutorial on particle filtering and smoothing: Fifteen years later. Handbook of Nonlinear Filtering, 12(656–704), 3., and it is the complement of my previous post.

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Particle Filtering and Smoothing

January 18, 2019 0 Comments

This note is for Doucet, A., & Johansen, A. M. (2009). A tutorial on particle filtering and smoothing: Fifteen years later. Handbook of Nonlinear Filtering, 12(656–704), 3. For the sake of clarity, I split the general SMC methods (section 3) into my next post.

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PLS in High-Dimensional Regression

January 15, 2019

This note is based on Cook, R. D., & Forzani, L. (2019). Partial least squares prediction in high-dimensional regression. The Annals of Statistics, 47(2), 884–908.

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Approximate $\ell_0$-penalized piecewise-constant estimate of graphs

January 13, 2019

This note is for Fan, Z., & Guan, L. (2018). Approximate $\ell_{0}$-penalized estimation of piecewise-constant signals on graphs. The Annals of Statistics, 46(6B), 3217–3245.

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Reversible jump Markov chain Monte Carlo

January 10, 2019

The note is for Green, P.J. (1995). “Reversible Jump Markov Chain Monte Carlo Computation and Bayesian Model Determination”. Biometrika. 82 (4): 711–732.

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Reconstruct Gaussian DAG

January 09, 2019

This note is based on Yuan, Y., Shen, X., Pan, W., & Wang, Z. (n.d.). Constrained likelihood for reconstructing a directed acyclic Gaussian graph. Biometrika.

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Link-free v.s. Semiparametric

January 08, 2019

This note is based on Li (1991) and Ma and Zhu (2012).

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Jackknife and Mutual Information

January 07, 2019

The jackknife is based on Wasserman (2006) and Efron and Hastie (2016), while the Jackknife estimation of Mutual Information is based on Zeng et al. (2018).

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Counting Process Based Dimension Reduction Methods for Censored Data

January 06, 2019

The note is for Sun, Q., Zhu, R., Wang, T., & Zeng, D. (2017). Counting Process Based Dimension Reduction Methods for Censored Outcomes. ArXiv:1704.05046 [Stat].

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SIR and Its Implementation

January 05, 2019 0 Comments

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Small World inside Large Metabolic Networks

January 02, 2019

The note is for Wagner, A., & Fell, D. A. (2001). The small world inside large metabolic networks. Proceedings of the Royal Society of London B: Biological Sciences, 268(1478), 1803-1810..

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Metabolic Network and Their Evolution

December 31, 2018

The note is for Chapter 2 of Soyer, Orkun S., ed. 2012 Evolutionary Systems Biology. Advances in Experimental Medicine and Biology, 751. New York: Springer.

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Evolutionary Systems Biology

December 30, 2018

The note is for Chapter 1 of Soyer, Orkun S., ed. 2012 Evolutionary Systems Biology. Advances in Experimental Medicine and Biology, 751. New York: Springer.

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Gibbs in genetics

August 24, 2018

The note is for Gilks, W. R., Richardson, S., & Spiegelhalter, D. (Eds.). (1995). Markov chain Monte Carlo in practice. CRC press..

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