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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：A method to deal with generalized linear regressions in big data
处理 大数据 广义线性回归
2023/4/28
This paper proposes a method to accelerate calculation for generalized linear models in big data. We separate the covariates of full model into several groups to build candidate models. In the process...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Fixed Effects Bayesian Testing in High-Dimensional Linear Mixed Models
高维 线性混合模型 固定效应 贝叶斯检验
2023/5/5
Hypothesis testing on high-dimensional fixed effects is indispensable for investigating the utility of the predictors on response. In this case, the conventional frequentist methods designed for cases...
中山大学岭南学院高级计量经济学课件（I：Nonparametric Econometrics）CH3 Semiparametric Partially Linear Model
中山大学岭南学院 高级计量经济学 课件（I：Nonparametric Econometrics） CH3 Semiparametric Partially Linear Model
2017/6/14
中山大学岭南学院高级计量经济学课件（I：Nonparametric Econometrics）CH3 Semiparametric Partially Linear Model。
Asymptotic equivalence for nonparametric generalized linear models
Nonparametric regression Statistical experiment De® - ciency distance Global white noise approximation Exponential family Variance stabilizing transformation
2015/8/25
We establish that a non-Gaussian nonparametric regression model is asymptotically equivalent to a regression model with Gaussian noise. The approximation is in the sense of Le Cam's de®- ciency d...
Functional Linear Discriminant Analysis for Irregularly Sampled Curves
Classification Filtering Functional data Linear discriminant analysis Low dimensional representation Reduced rank Regularized discriminant analysis Sparse curves
2015/8/21
We introduce a technique for extending the classical method of Linear Discriminant Analysis to data sets where the predictor variables are curves or functions. This procedure, which we call functional...
We study linear smoothers and their use in building nonparametric regression models. In the first part of this paper we examine certain aspects of linear smoothers for scatterplots; examples of these ...
Generalized linear and generalized additive models in studies of species distributions:setting the scene
Statistical modeling Generalized linear model Generalized additive model Species distribution Predictive modeling
2015/8/21
An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we intro...
L1-regularization path algorithm for generalized linear models
Generalized linear model Lasso Path algorithm Predictor–corrector method Regularization Variable selection
2015/8/21
We introduce a path following algorithm for L1-regularized generalized linear models. The L 1-regularization procedure is useful especially because it, in effect, selects variables according to the am...
Regularized linear discriminant analysis and its application in microarrays
Regularized linear discriminant analysis microarrays
2015/8/21
In this paper, we introduce a modified version of linear discriminant analysis, called the “shrunken centroids regularized discriminant analysis” (SCRDA). This method generalizes the idea of the “near...
Polygenic Modeling with Bayesian Sparse Linear Mixed Models
Polygenic Modeling Bayesian Sparse Linear Mixed Models
2012/11/23
Both linear mixed models (LMMs) and sparse regression models are widely used in genetics applications, including, recently, polygenic modeling in genome-wide association studies. These two approaches ...
Learning Linear Bayesian Networks with Latent Variables
Linear Networks Bayesian Latent Variables
2012/11/23
This work considers the problem of learning linear Bayesian networks when some of the variables are unobserved. Identifiability and efficient recovery from low-order observable moments are established...
Minimax adaptive tests for the Functional Linear model
Functional linear regression eigenfunction principal com-ponent analysis adaptive testing minimax hypothesis testing
2012/6/21
We introduce two novel procedures to test the nullity of the slope function in the functional linear model with real output. The test statistics combine multiple testing ideas and random projections o...
Estimation in high-dimensional linear models with deterministic design matrices
Identifiability projection ridge regression sparsity thresholding variable selection
2012/6/21
Because of the advance in technologies, modern statistical studies often encounter linear models with the number of explanatory variables much larger than the sample size. Estimation and variable sele...
Lossless Linear Compression of Data with Minimal Dimension in Linear Minimum Variance Estimation
LMV estimation lossless compression linear transformation singular value
2011/11/11
Consider a Linear Minimum Variance (LMV) estimation problem where the linear transformation of data is needed to compress dimension of observation data without loss of performance. A necessary and su±...
An Adaptive Semiparametric Estimation for Partially Linear Models
Partially linear model adaptability adjustment
2011/11/11
In this paper, we propose an adaptive semiparametric estimation for the nonparametric component of partially linear models. The new estimator is better than the usual nonparametric method in the sense...