Stochastic processes with heavy tails and temporal dependence: modeling, probabilistic properties and statistical inference
具有重尾和时间依赖性的随机过程:建模、概率属性和统计推断
基本信息
- 批准号:356036-2013
- 负责人:
- 金额:$ 1.38万
- 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:2015
- 资助国家:加拿大
- 起止时间:2015-01-01 至 2016-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
A classical assumption in probability and statistics is that random variables (data) are independent and
approximately Gaussian. On the other hand, it is commonly observed that many types of data that occur in
finance, environmental sciences or network traffic are in fact far away from being independent and Gaussian.
This motivates modeling of such data using time series and complicated stochastic processes that can capture heavy tails, weak or strong dependence, and self-similarity.
In this project we will study probabilistic properties and statistical inference for discrete and continuous time
series and stochastic processes that arise in applied probability and applied statistics. We will focus on the
following aspects:
a) Modeling tails and memory in discrete and continuous time series models.
b) Probabilistic properties and statistical analysis of network traffic models.
概率和统计学中的一个经典假设是随机变量(数据)是独立的,
近似高斯。另一方面,通常可以观察到,
金融、环境科学或网络流量实际上还远未独立和高斯。
这促使使用时间序列和复杂的随机过程来建模这些数据,这些过程可以捕获重尾,弱或强相关性和自相似性。
在本项目中,我们将研究离散和连续时间的概率属性和统计推断
应用概率和应用统计中出现的序列和随机过程。重点抓好
以下几个方面:
a)离散和连续时间序列模型中的尾部和记忆建模。
B)网络流量模型的概率特性和统计分析。
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)
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Kulik, Rafal其他文献
HEAVY-TAILED BRANCHING PROCESS WITH IMMIGRATION
- DOI:
10.1080/15326349.2013.838508 - 发表时间:
2013-10-02 - 期刊:
- 影响因子:0.7
- 作者:
Basrak, Bojan;Kulik, Rafal;Palmowski, Zbigniew - 通讯作者:
Palmowski, Zbigniew
Kulik, Rafal的其他文献
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{{ truncateString('Kulik, Rafal', 18)}}的其他基金
Probabilistic Properties and Statistical Inference for Regularly Varying Time Series
规律变化的时间序列的概率性质和统计推断
- 批准号:
RGPIN-2018-04156 - 财政年份:2022
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
Probabilistic Properties and Statistical Inference for Regularly Varying Time Series
规律变化的时间序列的概率性质和统计推断
- 批准号:
RGPIN-2018-04156 - 财政年份:2021
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
Probabilistic Properties and Statistical Inference for Regularly Varying Time Series
规律变化的时间序列的概率性质和统计推断
- 批准号:
RGPIN-2018-04156 - 财政年份:2020
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
Probabilistic Properties and Statistical Inference for Regularly Varying Time Series
规律变化的时间序列的概率性质和统计推断
- 批准号:
RGPIN-2018-04156 - 财政年份:2019
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
Probabilistic Properties and Statistical Inference for Regularly Varying Time Series
规律变化的时间序列的概率性质和统计推断
- 批准号:
RGPIN-2018-04156 - 财政年份:2018
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
Stochastic processes with heavy tails and temporal dependence: modeling, probabilistic properties and statistical inference
具有重尾和时间依赖性的随机过程:建模、概率属性和统计推断
- 批准号:
356036-2013 - 财政年份:2017
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
Stochastic processes with heavy tails and temporal dependence: modeling, probabilistic properties and statistical inference
具有重尾和时间依赖性的随机过程:建模、概率属性和统计推断
- 批准号:
356036-2013 - 财政年份:2016
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
Stochastic processes with heavy tails and temporal dependence: modeling, probabilistic properties and statistical inference
具有重尾和时间依赖性的随机过程:建模、概率属性和统计推断
- 批准号:
356036-2013 - 财政年份:2014
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
Stochastic processes with heavy tails and temporal dependence: modeling, probabilistic properties and statistical inference
具有重尾和时间依赖性的随机过程:建模、概率属性和统计推断
- 批准号:
356036-2013 - 财政年份:2013
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
Statistics for long range dependent sequences
长程相关序列的统计
- 批准号:
356036-2008 - 财政年份:2012
- 资助金额:
$ 1.38万 - 项目类别:
Discovery Grants Program - Individual
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