[影像處理] [財務數學] [連續型馬可夫鍊模型在疾病發展史的應用]
主辦單位:台大數學系,中研院統計所
協辦單位:國科會數學研究推動中心
期間:自89年2月1日至89年7月31日止
主題:
一、影像處理:
主持人:傅承德(中研院統計所)、陳宏(台大數學系)
協同主持人:盧鴻興(交大統計學研究所)
、鄭少為(中研院統計所)
「認購權證理論與計算」研討會:香港科技大學財務學系
段錦泉教授主講
三、連續型馬可夫鍊模型在疾病發展史的應用。
主持人:傅承德(中研院統計所)、陳宏(台大數學系)
協同主持人:趙維雄(中研院統計所)
Introduction to the basic modeling of three medical imaging systems: PET (Positron Emission Tomography), fMRI (functional Magnetic Resonance Images), and Ultrasound Images.
Asymptotic consistency of the maximum likelihood estimate in positron emission tomography and applications
盧鴻興教授(交大統計科學研究所) abstract transparency
Some Statistical Analysis in PET (Positron Emission Tomography) and Ultrasound Images.
An Introduction to Statistical Image Analysis using Markov Random Fields
主講人:UCLA統計系吳英年助理教授
時間: 六月 24日至七月7日。
主題一:EM/data augmentation 6/27/2000 abstract
「財務工程簡介」課程
時 間:2000年3月11日(星期六)上午8:20至下午4:40
地 點:台北市台灣大學新數學館101教室
主辦單位:中華機率統計學會
協辦單位:台灣大學國際金融研究所國際金融研究中心、台灣大學數學系
課程主題
First Generation Option | ||
中央大學
財務管理學系 |
8:40-9:30 | Introduction to Financial Engineering |
10:00-10:50 | Equivalent Martingale Measures and Risk Neutral Pricing | |
11:00-11:50 | Alternative Option Pricing Models | |
Second Generation Option | ||
中央大學
財務管理學系 |
13:30-14:20 | Term Structure Models for Interest Rates |
14:50-15:40 | Interest Rate Derivatives | |
15:50-16:40 | Exotic Options |
聯絡人:陳宏 教授, 106台北市羅斯福路四段一號「台灣大學數學系陳宏」
Tel:02–23633860 ext 109 Fax:02-23914439
E-mail:hchen@math.ntu.edu.tw
註冊費: 教師:1,500元,學生:1,000元,一般:5,000元
註:採線上註冊方式,中華機率統計學會永久會員,註冊費減收500元,
中華機率統計學會一般會員,註冊費收據可抵免本年度學會會費
如您想進一步瞭解財務工程此領域,可參看Hull的書,以下是由Hull網站上取得之投影片(需UNZIP檔案)
hullslid1.exehullslid2.exe
hullslid3.exe
主講人: Hong Kong University
of Science and Technology 財務學系段錦泉教授
(Senior Wei Lun Fellow)
時間:三月十九日至二十三日
地點:台大數學系308室
主講人: 段錦泉教授(Senior Wei Lun Fellow)香港科技大學財務學系研 討 會 議 程
三月二十一日(星期二)
8:30-10:00 Derivative securities
pricing theories (I) transparency
10:30-12:00 Derivative securities
pricing theories (II) transparency
abstract
三月二十二日(星期三)
8:30-10:00 Numerical methods
for valuing derivative securities (I) transparency
10:30-12:00 Numerical methods for
valuing derivative securities (II) transparency
abstract
演講人:
三月二十一日(星期二)
14:00-15:00 何淮中教授(中央研究院統計科學研究所)abstract
講題:Modeling financial time
series
15:30-16:30 廖四郎教授(政治大學金融學系)
abstract
講題:Theory of Dynamic Capital
Structure and The Valuation
of Corporate Bonds Second Generation Option
三月二十二日(星期三)
13:30-14:30 林建甫教授(台灣大學經濟學系)abstracttransparency
講題:Modeling volatility in
the financial data
14:30-15:30 呂育道教授(台灣大學資訊工程學系)
transparency
講題:Computational techniques
in derivatives pricing
四月份後續活動
演講人:
五月份舉行
演講人:
5/11/2000 趙維雄(中央研院統計科學研究所)
講題:Trend
Analysis of Longitudinal Ordinal Data with Irregular Timing
Abstract: In
many longitudinal studies, repeated observations of multivariate ordinal
outcomes along with several covariates are taken from a sample of
subjects at irregular time points, resulting in multivariate longitudinal
ordinal data. When the outcome fluctuates over time before entering an
absorbing state, it is often of interest to investigate the relationship
between the trend of the underlying outcome process and the covariates.
One of the proposed models available for trend analysis without absorption
is the univariate local equilibrium distribution model of Kosorok and Chao
(1996). In this talk, we extend their model to a multivariate model for
multivariate outcomes. Odds ratios are used to measure the cross-sectional
association among outcomes that are observed at the same time.
Extenstion feasibility is examined from the estimation point of view. If
time permits, a univariate extension to allow for a single absorbing state
will also be introduced.
5/17/2000 鄧利源 (University of Memphis)
講題:
Markov Chain Monte Carlo: Metropolis Algorithm, Gibbs Sampling and Some
Applications
Abstract: In
this talk, we will start with an example, Genetic Linkage Model, to motivate
various Markov Chain Monte Carlo (MCMC) methods. In particular, we will
use the example to illustrate the use of EM algorithm, Metropolis algorithm,
and Metropolis-Hastings Method. We will discuss their connection with the
standard Rejection method in random variate generation. Finally, we give
another example to illustrate the foundation, the procedure and some applications
of Gibbs sampling.
5/18/2000 張淑惠(國立台灣大學流行病學研究所)
講題:Regression Methods for Recurrent Event Data
5/25/2000 葉瑞徽(台灣科技大學工業管理系)
講題:The
Applications of Acyclic Phase-Type Distributions on Semi-Markov Decision
Processes
Abstract: It
is well-known that the main barrier in analyzing semi-Markovian model is
that the mathematical formulation is so complicated that it is essentially
intractable. To overcome this barrier, an acyclic phase-type approach is
proposed to approximate the general sojourn time distributions of a semi-Markov
process. Using the approximation, a semi-Markovian model can be transformed
into a Markovian model such that the analytical tractability of Markov
processes can be preserved. Based on the resulting Markovian model, algorithms
are provided to derive the optimal state-dependent and state-age-dependent
policies. Furthermore, procedures are developed to implement these
optimal policies back on the original semi-Markovian model.