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)
Continuous Time Markov Chain
February 20, 2019
This note is based on Karl Sigman’s IEOR 6711: Continuous-Time Markov Chains.
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.
Presistency
February 18, 2019
The paper, Greenshtein and Ritov (2004), is recommended by Larry Wasserman in his post Consistency, Sparsistency and Presistency.
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.
Deep Learning
February 16, 2019
This note is based on LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.
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.
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.
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.
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.
Comparisons of Three Likelihood Criteria
February 12, 2019
The First Glimpse into Pseudolikelihood
February 12, 2019
This post caught a glimpse of the pseudolikelihood.
Calculating Marginal likelihood
January 30, 2019
Annealed Importance Sampling
January 28, 2019
This is the note for Neal, R. M. (1998). Annealed Importance Sampling. ArXiv:Physics/9803008.
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].
The Kalman Filter and Extended Kalman Filter
January 21, 2019
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.
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.
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.
Approximate $\ell_0$-penalized piecewise-constant estimate of graphs
January 13, 2019
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.
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.
Link-free v.s. Semiparametric
January 08, 2019
This note is based on Li (1991) and Ma and Zhu (2012).
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).
Counting Process Based Dimension Reduction Methods for Censored Data
January 06, 2019
SIR and Its Implementation
January 05, 2019 0 Comments
Small World inside Large Metabolic Networks
January 02, 2019
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.
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.
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..