reading review

0.1 reviews 1 in April,2019

Time period and Work

Elements of statistical learning

Index:

  • Chap2 Supervised learning
  • Chap3 Linear methods for Regression
  • Chap4 Linear Methods for Classification
  • Chap5 Basic Expansions and Regularization
    • Nonparametric Regression and Generalized Linear Methods
      • Chap1. Introduction
      • Chap2. Interpolating and smoothing splines
  • Chap7 Model assessment and Selection
  • Chap8 Model Inference and Averaging
  • Chap9 Additive Models, Trees, and Related Methods
    • Generalized Additive Model: Chap2 Smoothing

Mixed models,theory and applications with R

Eugene Demidenko

to page 98, Chap1. Introduction: Why Mixed Models Chap2. MLE for the LME model

Classification and Regression Trees

LeiBreiman

To Chap2.

An Introduction to Graphical Models, (lecture notes)

To Chap4

Michael I. Jordan

Gaussian Process for machine learning

Modelling Dependence with copula, and application to risk management (Lecture notes)

  • Least-Angle regression,(Efron et al. 2004)

  • Elastic Net (Zou and Hastie 2005)

  • Random effect selection(Pan and Huang 2013)
  • Jmcm (Pan and Pan 2017)
  • mcd: (Pourahmadi 2000) , (Pourahmadi 1999) , (Pan and MacKenzie 2003) and (J. Pan and MacKenzie 2006)

  • acd& Bayesian random effect selection : (Chen, Biometrics, and 2003, n.d.)

  • Covariance matrix estimation (Bickel and Levina 2008),(Pinheiro and Bates 1996),

Covariance modelling talks by Pourhamadi

Regulized covariance estimating, banding (Rothman, Levina, and Zhu 2010),(Lee and Lin 2018),(Cheng, Zhang, and Zhang 2017),(An, Guo, and Liu 2014)

Bayes random effect selection (Cai, Biometrics, and 2006, n.d.)

lasso uniqueness (Tibshirani 2014)

Discrete correlated data analysis via copula (Tang, Zhang, and Leng 2019) and (Song et al., n.d.)

Gaussian Process(Dunlop et al. 2017)

Recent reading roptim, by Yi Pan

acd:(Maadooliat et al., n.d.)

Joint modelling dealing with non-ignorance missing data (Bhuyan, n.d.)

Penalised method: (Fan and Li 2001)

mcd for \(\Sigma\) (Zhang and Leng 2012), and it’s gee (Liu, Mathematics, and 2013, n.d.)

mcd gee (J. Pan and Ye 2006)

HPC: (Zhang, Leng, and Tang 2015),(Rapisarda, Brigo, and Mercurio 2007)

References

Efron, Bradley, Trevor Hastie, Iain Johnstone, and Robert Tibshirani. 2004. “Least Angle Regression.” The Annals of Statistics, 1–41.

Zou, Hui, and Trevor Hastie. 2005. “Regularization and variable selection via the elastic net.” Journal of the Royal Statistical Society: Series B (Statistical Methodology), February, 1–20.

Pan, Jianxin, and Chao Huang. 2013. “Random effects selection in generalized linear mixed models via shrinkage penalty function.” Statistics and Computing 24 (5): 725–38.

Pan, Jianxin, and Yi Pan. 2017. “jmcm: An RPackage for Joint Mean-Covariance Modeling of Longitudinal Data.” Journal of Statistical Software 82 (9): 1–29.

Pourahmadi, Mohsen. 2000. “Maximum likelihood estimation of generalised linear models for multivariate normal covariance matrix.” Biometrika 87 (2): 425–35.

Pourahmadi, Mohsen. 1999. “Joint mean-covariance models with applications to longitudinal data: Unconstrained parameterisation.” Biometrika, September, 1–14.

Pan, Jianxin, and Gilbert MacKenzie. 2003. “On modelling mean-covariance structures in longitudinal studies,” February, 1–6.

Pan, Jianxin, and Gilbert MacKenzie. 2006. “Regression models for covariance structures in longitudinal studies.” Statistical Modelling: An International Journal 6 (1): 43–57.

Chen, Z, DB Dunson Biometrics, and 2003. n.d. “Random effects selection in linear mixed models.” Wiley Online Library.

Bickel, Peter J, and Elizaveta Levina. 2008. “Regularized estimation of large covariance matrices.” The Annals of Statistics 36 (1): 199–227.

Pinheiro, Jos C, and Douglas M Bates. 1996. “Unconstrained parametrizations for variance-covariance matrices.” Statistics and Computing 6 (3): 289–96.

Rothman, Adam J, Elizaveta Levina, and Ji Zhu. 2010. “A new approach to Cholesky-based covariance regularization in high dimensions.” Biometrika 97 (3): 539–50.

Lee, Kyoungjae, and Lizhen Lin. 2018. “Bayesian Test and Selection for Bandwidth of High-dimensional Banded Precision Matrices.” arXiv.org, April. http://arxiv.org/abs/1804.08650v1.

Cheng, Guanghui, Zhengjun Zhang, and Baoxue Zhang. 2017. “Test for bandedness of high-dimensional precision matrices,” November, 1–20.

An, Baiguo, Jianhua Guo, and Yufeng Liu. 2014. “Hypothesis testing for band size detection of high-dimensional banded precision matrices.” Biometrika 101 (2): 477–83.

Cai, B, DB Dunson Biometrics, and 2006. n.d. “Bayesian covariance selection in generalized linear mixed models.” Wiley Online Library.

Tibshirani, Ryan J. 2014. “The Lasso Problem and Uniqueness,” April, 1–27.

Tang, Cheng Yong, Weiping Zhang, and Chenlei Leng. 2019. “Discrete Longitudinal Data Modeling with a Mean-Correlation Regression Approach.” Statistica Sinica.

Song, PXK, M Li, Y Yuan Biometrics, and 2009. n.d. “Joint regression analysis of correlated data using Gaussian copulas.” Wiley Online Library.

Dunlop, Matthew M, Mark A Girolami, Andrew M Stuart, and Aretha L Teckentrup. 2017. “How Deep Are Deep Gaussian Processes?” arXiv.org, November. http://arxiv.org/abs/1711.11280v2.

Maadooliat, M, M Pourahmadi, JZ Huang Statistics Computing, and and 2013. n.d. “Robust estimation of the correlation matrix of longitudinal data.” Springer.

Bhuyan, Prajamitra. n.d. “Estimation of random-effects model for longitudinal data with nonignorable missingness using Gibbs sampling.” Computational Statistics.

Fan, Jianqin, and Runze Li. 2001. “Variable selection via nonconcave penalized likelihood and its oracle properties.” Journal of the American Statistical Association, December.

Zhang, W, and C Leng. 2012. “A moving average Cholesky factor model in covariance modelling for longitudinal data.” Biometrika 99 (1): 141–50.

Liu, X Y, WP Zhang Science China Mathematics, and 2013. n.d. “A moving average Cholesky factor model in joint mean-covariance modeling for longitudinal data.” Springer.

Pan, Jianxin, and Huajun Ye. 2006. “Modelling of covariance structures in generalised estimating equations for longitudinal data.” Biometrika 93 (4): 927–41.

Zhang, Weiping, Chenlei Leng, and Cheng Yong Tang. 2015. “A joint modelling approach for longitudinal studies.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 77 (1): 219–38.

Rapisarda, Francesco, Damiano Brigo, and Fabio Mercurio. 2007. “Parameterizing correlations: a geometric interpretation.” IMA Journal of Management Mathematics 18 (1): 55–73.