搜索结果: 1-9 共查到“知识库 环境与生态统计学其他学科”相关记录9条 . 查询时间(8.03 秒)
中国科学院城市环境研究所等构建出冷室气体响应边界变点模型（图）
冷室气体 应边界变点 关键变量关系模型
2022/9/21
关键变量关系模型拟合是解析生物与环境相互作用机制的基本统计学路径之一。根据生物与环境相互作用机制，拟合构建的模型可分为两类，一是环境变化对生物动态的影响模型，例如可利用这类影响模型解析水体营养盐变化对浮游植物生物量动态的调控机制；二是生物对环境的驱动模型，例如可利用这类驱动模型解析浮游植物代谢活动对水体环境与大气环境关联物质的驱动机制。统计学方法和工具创新及野外环境原位观测数据增加，使生物与环境相...
中南林业科技大学生态文化与环境政策研究所成立于2017年，研究所挂靠在中南林业科技大学马克思主义学院，研究所负责人为傅晓华教授。
An estimation of distribution algorithm with adaptive Gibbs sampling for unconstrained global optimization
Estimation of distribution algorithms Evolutionary algorithms
2011/7/19
In this paper is proposed a new heuristic approach belonging to the field of evolutionary Estimation of Distribution Algorithms (EDAs). EDAs builds a probability model and a set of solutions is sample...
Statistical methods of SNP data analysis with applications
Genetic data statistical analysis multifactor dimensiona-lity reduction
2011/7/7
Various statistical methods important for genetic analysis are considered and developed. Namely, we concentrate on the multifactor dimensionality reduction, logic regression, random forests and stocha...
Optimal Rate Scheduling via Utility-Maximization for J-User MIMO Markov Fading Wireless Channels with Cooperation
Processor-SharingQueues Random Environment Multi-Input Multi-Output
2011/7/7
We design a dynamic rate scheduling policy of Markov type via the solution (a social optimal Nash equilibrium point) to a utility-maximization problem over a randomly evolving capacity set for a class...
Markov Chain Monte Carlo Based on Deterministic Transformations
Geostatistics High dimension Inverse transfromation Jacobian
2011/7/6
In this article we propose a novel MCMC method based on deterministic transformations T : X x D --> X where X is the state-space and D is some set which may or may not be a subset of X. We refer to ou...
Nonasymptotic bounds on the estimation error of MCMC algorithms
Mean square error Computable bounds
2011/7/6
We address the problem of upper bounding the mean square error of MCMC estimators. Our analysis is non-asymptotic.
Bayesian Sparsity-Path-Analysis of Genetic Association Signal using Generalized t Priors
Bayesian Sparsity-Path-Analysis Genetic Association Signal
2011/7/5
We explore the use of generalized t priors on regression coefficients to help understand the nature of association signal within "hit regions" of genome-wide association studies.
Deriving chemosensitivity from cell lines: Forensic bioinformatics and reproducible research in high-throughput biology
Microarrays, reproducibility forensic bioinformatics
2010/10/19
High-throughput biological assays such as microarrays let us ask very detailed questions about how diseases operate, and promise to let us personalize therapy. Data processing, however, is often not d...