Ecological modeling via differential equations and optimal inference strategies
通过微分方程和最优推理策略进行生态建模
基本信息
- 批准号:327006-2009
- 负责人:
- 金额:$ 1.09万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2013
- 资助国家:加拿大
- 起止时间:2013-01-01 至 2014-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This proposal deals with three areas and all revolve around optimal inference in switching models and generalized inference. First, I will consider an inference problem in some regime switching stochastic processes such as the process of the interest rate structure. For many cases, the maximum likelihood estimator (MLE) does not have a closed form and thus, much progress is to be made in the asymptotic properties of the suggested MLE. I plan to study the asymptotic properties of the MLEs and to investigate some alternative methods which are based for example on quasi-likelihood technique. Further, I will explore extensions to multiple multivariate stochastic processes with regime switching when the components of the parameter matrix are suspected to lie in a special hyper-plan. Further, as in Nkurunziza and Ahmed (2008), I will improve classical MLE by pretest and shrinkage estimators. Second, I consider inference problems for the parameters of k time-varying deterministic systems of differential equations (ODEs) which describe the dynamic of k pairs of prey-predator populations as for example time-varying Lotka-Volterra and Holling-Tanner ODEs. Interestingly, by such time varying coefficients, the model account for the animal adaptation factor, the hiding strategy and seasonal effects. In this project, I will also study the case where the error noise structure is more general than that considered in Froda and Nkurunziza (2007) along with regime switching, and I hope to improve the previous methods by using shrinkage and pretest strategies. Finally, some classical inference problems are to be revisited through generalized inference that is proved to give satisfactory results for a variety of complex problems such as Behrens-Fisher problem. I plan on extending the research work in Nkurunziza and Chen (2008), and in Nkurunziza, Quazi and Fung (2008) where the generalized inference is studied through the invariance principle, and applied to some linear models. Namely, I will consider the case of a regime-switching linear models with heteroscedastic error terms and/or the case of exogenous stochastic variables. Finally, I will investigate an alternative of Chow test for testing the regime change.
这项建议涉及三个方面,都围绕着切换模型中的最优推理和广义推理。首先,我将考虑一些制度转换随机过程中的一个推断问题,例如利率结构的过程。对于许多情况,极大似然估计(MLE)不具有封闭形式,因此,在所建议的极大似然估计的渐近性质方面有很大的进展。我计划研究最大似然估计的渐近性质,并研究一些替代方法,例如基于拟似然技术的方法。进一步,我将探索当参数矩阵的分量被怀疑位于一个特殊的超计划中时,具有制度切换的多个多变量随机过程的扩展。此外,就像在Nkurunziza和Ahmed(2008)中一样,我将通过预测检验和收缩估计来改进经典的最大似然估计。其次,考虑了描述k对捕食者种群动态的k个时变确定性微分方程组(ODE)的参数推断问题,例如时变Lotka-Volterra和Holling-Tanner微分方程组。有趣的是,通过这种时变系数,该模型考虑了动物适应因素、隐藏策略和季节性影响。在这个项目中,我还将研究误差噪声结构比Froda和Nkurunziza(2007)所考虑的结构更一般的情况,并希望通过使用收缩和预测测试策略来改进以前的方法。最后,通过广义推理,对一些经典的推理问题进行了重新讨论,证明它对诸如Behrens-Fisher问题等各种复杂问题都有令人满意的结果。我计划扩展Nkurunziza和Chen(2008)以及Nkurunziza,Quazi和Fong(2008)的研究工作,通过不变原理研究广义推理,并将其应用于一些线性模型。也就是说,我将考虑具有异方差误差项的制度转换线性模型的情况和/或外部随机变量的情况。最后,我将研究一种替代的周测试来测试政权的变化。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Nkurunziza, Sévérien其他文献
Nkurunziza, Sévérien的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Nkurunziza, Sévérien', 18)}}的其他基金
Modeling and Optimal Inference in change-point models with ultra-high dimensional data
超高维数据变点模型的建模和优化推理
- 批准号:
RGPIN-2019-04464 - 财政年份:2022
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Modeling and Optimal Inference in change-point models with ultra-high dimensional data
超高维数据变点模型的建模和优化推理
- 批准号:
RGPIN-2019-04464 - 财政年份:2021
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Modeling and Optimal Inference in change-point models with ultra-high dimensional data
超高维数据变点模型的建模和优化推理
- 批准号:
RGPIN-2019-04464 - 财政年份:2020
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Modeling and Optimal Inference in change-point models with ultra-high dimensional data
超高维数据变点模型的建模和优化推理
- 批准号:
RGPIN-2019-04464 - 财政年份:2019
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2018
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2017
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2016
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Evaluating and improving a probabilistic threat assessment algorithm
评估和改进概率威胁评估算法
- 批准号:
500261-2016 - 财政年份:2016
- 资助金额:
$ 1.09万 - 项目类别:
Engage Grants Program
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2015
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2014
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
相似国自然基金
Galaxy Analytical Modeling
Evolution (GAME) and cosmological
hydrodynamic simulations.
- 批准号:
- 批准年份:2025
- 资助金额:10.0 万元
- 项目类别:省市级项目
页岩超临界CO2压裂分形破裂机理与分形离散裂隙网络研究
- 批准号:
- 批准年份:2020
- 资助金额:0.0 万元
- 项目类别:省市级项目
非管井集水建筑物取水机理的物理模拟及计算模型研究
- 批准号:40972154
- 批准年份:2009
- 资助金额:41.0 万元
- 项目类别:面上项目
微生物发酵过程的自组织建模与优化控制
- 批准号:60704036
- 批准年份:2007
- 资助金额:21.0 万元
- 项目类别:青年科学基金项目
ABM有效性检验的关键技术研究
- 批准号:70701001
- 批准年份:2007
- 资助金额:18.0 万元
- 项目类别:青年科学基金项目
三峡库区以流域为单元森林植被对洪水影响研究
- 批准号:30571486
- 批准年份:2005
- 资助金额:25.0 万元
- 项目类别:面上项目
相似海外基金
Collaborative Research: Modeling organismal responses to changing ecological regimes via investigation of stress, growth and reproduction in the longest-lived mammal
合作研究:通过研究最长寿哺乳动物的压力、生长和繁殖,模拟生物体对不断变化的生态状况的反应
- 批准号:
2122890 - 财政年份:2021
- 资助金额:
$ 1.09万 - 项目类别:
Continuing Grant
Collaborative Research: Modeling organismal responses to changing ecological regimes via investigation of stress, growth and reproduction in the longest-lived mammal
合作研究:通过研究最长寿哺乳动物的压力、生长和繁殖,模拟生物体对不断变化的生态状况的反应
- 批准号:
2122889 - 财政年份:2021
- 资助金额:
$ 1.09万 - 项目类别:
Continuing Grant
Elucidating ecological mechanisms for propagation of antibiotic resistance genes via massively parallelized single-cell sequencing
通过大规模并行单细胞测序阐明抗生素抗性基因传播的生态机制
- 批准号:
10362535 - 财政年份:2021
- 资助金额:
$ 1.09万 - 项目类别:
Collaborative Research: Modeling organismal responses to changing ecological regimes via investigation of stress, growth and reproduction in the longest-lived mammal
合作研究:通过研究最长寿哺乳动物的压力、生长和繁殖,模拟生物体对不断变化的生态状况的反应
- 批准号:
2122888 - 财政年份:2021
- 资助金额:
$ 1.09万 - 项目类别:
Continuing Grant
Modeling Secondary School STEM Teacher Retention via Ecological Theories
通过生态理论模拟中学 STEM 教师保留率
- 批准号:
1949530 - 财政年份:2020
- 资助金额:
$ 1.09万 - 项目类别:
Standard Grant
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2018
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2017
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2016
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2015
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Optimal Inference in model subject to changes and modeling in ecological systems via differential equations
受变化影响的模型的最优推理以及通过微分方程对生态系统进行建模
- 批准号:
RGPIN-2014-06430 - 财政年份:2014
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual














{{item.name}}会员




