搜索结果: 1-15 共查到“Variable selection”相关记录51条 . 查询时间(0.109 秒)
Nonlinear mixed-effects scalar-on-function models and variable selection
Canonical correlation Functional least angle regression (fLARS) Gaussian process prior Movement data Scalar-on-function regression Variable selection
2024/1/11
This paper is motivated by our collaborative research and the aim is to model clinical assessments of upper limb function after stroke using 3D-position and 4D-orientation movement data. We present a ...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Variable selection for generalized linear models with interval-censored failure time data
区间删失 失效时间数据 广义线性模型 变量选择
2023/5/9
Variable selection is often needed in many fields and has been discussed by many authors in various situations.
Spectrometric prediction of wood basic density by comparison of different grain angles and variable selection methods
Spectrometric prediction wood basic density
2023/6/2
Background:Wood basic density (WBD) is one of the most crucial wood property in tree and mainly determined the end use of wood for industry. However, the measurement WBD is time- and cost-consuming, w...
VARIABLE SELECTION FOR ROAD SEGMENTATION IN AERIAL IMAGES
Classification Feature Selection Logistic Regression Random Forests Road Extraction
2017/7/12
For extraction of road pixels from combined image and elevation data, Wegner et al. (2015) proposed classification of superpixels into road and non-road, after which a refinement of the classification...
Factor profiling for ultra high dimensional variable selection
Bayesian Information Criterion Factor Profiling Forward Re- gression Maximum Eigenvalue Ratio Criterion Profiled Independent Screening
2016/1/19
We propose here a novel method of factor profiling (FP) for ultra high dimen-sional variable selection. The new method assumes that the correlation structure of the high dimensional data can be well r...
Regularization and variable selection via the elastic net
Grouping effect LARS algorithm Lasso Penalization p>n problem Variable selection
2015/8/21
We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar s...
SLOPE – Adaptive Variable Selection via Convex Optimization
Sparse regression variable selection false discovery rate lasso sorted `1 penalized estimation (SLOPE)
2015/6/17
We introduce a new estimator for the vector of coefficients β in the linear model y = Xβ +z, where X has dimensions n × p with p possibly larger than n. SLOPE, short for Sorted L-One Penalized Estimat...
Variable selection and structural discovery in joint models of longitudinal and survival data
Joint models Mixed effect selection Structural discovery Adaptive LASSO Gaussian quadrature EM algorithm
2015/5/21
Joint models of longitudinal and survival outcomes have been used with increasing frequency in clinical investigations. Correct specification of fixed and random effects, as well as their functional f...
Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
Coordinate descent counts data overdispersion regularized likelihood sparse group penalty
2013/6/14
With the development of next generation sequencing technology, researchers have now been able to study the microbiome composition using direct sequencing, whose output are bacterial taxa counts for ea...
Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
Coordinate descent counts data overdispersion regularized likelihood sparse group penalty
2013/6/14
With the development of next generation sequencing technology, researchers have now been able to study the microbiome composition using direct sequencing, whose output are bacterial taxa counts for ea...
Sharp Variable Selection of a Sparse Submatrix in a High-Dimensional Noisy Matrix
estimation minimax testing random matrices selection of sparse signal sharp selection bounds variable selection
2013/4/28
We observe a $N\times M$ matrix of independent, identically distributed Gaussian random variables which are centered except for elements of some submatrix of size $n\times m$ where the mean is larger ...
Variable Selection for Clustering and Classification
Classication Cluster analysis High-dimensional data Mixture models Model-based clus-tering Variable selection
2013/4/28
As data sets continue to grow in size and complexity, effective and efficient techniques are needed to target important features in the variable space. Many of the variable selection techniques that a...
Criteria for Bayesian model choice with application to variable selection
Model selection variable selection objective Bayes.
2012/11/23
In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propos...
Criteria for Bayesian model choice with application to variable selection
Model selection variable selection objective Bayes.
2012/11/23
In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propos...
Bayesian variable selection for spatially dependent generalized linear models
generalized linear models variable selection Bayesian spatially
2012/11/22
Despite the abundance of methods for variable selection and accommodating spatial structure in regression models, there is little precedent for incorporating spatial dependence in covariate inclusion ...