Browsing by Author "Chan, WY"

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A minimum-cost strategy for cluster recruitment
(2000)
Chan, WY
;
Peng, NF
;
統計學研究所
;
Institute of Statistics
It is becoming increasingly common for the design of a clinical study to involve cluster samples. Very few researches investigated the appropriate number of clusters. None of them treat cluster size and the number of clusters as random variables. In reality, the recruitment of clusters can not be reached at one time and the cluster sizes are usually random. The longer the recruitment takes the more expensive the total study costs will be. This paper provides a strategy for sequential recruitment of clusters, which can minimize the total study cost. By treating the number of additional observational subjects required at each time point as a Markov Chain, we derive an iterative procedure for optimal strategy and study the property of this strategy, especially the duration of the cluster recruitment. This strategy is also extended to search for an optimal number of centers in a multi-center clinical trial.
Continuous time Markov chains observed on an alternating renewal process with exponentially distributed durations
(2006-02-15)
Chan, WY
;
Peng, NF
;
統計學研究所
;
Institute of Statistics
A continuous time Markov chain observed on a system following the dynamic behavior of an alternating renewal process is studied. This alternating renewal process is assumed to have exponentially distributed durations. The limiting behavior of the process is examined. Examples of applications are given. (c) 2005 Published by Elsevier B.V.
Tensor product polynomial splines
(1997-01-01)
Chen, LA
;
Chan, WY
;
Lee, TS
;
統計學研究所
;
Institute of Statistics
This paper presents a unified study of smoothing tensor product piecewise polynomials as tensor product polynomial splines. This study generalizes the theory of univariate polynomial splines of Poirier (1973) and Smith (1979) to the multivariate setting, and the method proposed herein provides various spline bases that gives great flexibility for selecting models. An example analyzing an Australia wine industry data shows simple tensor product spline can capture the trend in the data appropriately to law of economics whereas multiple lineal model fails in capturing the trend (see Maddala (1988)).
Tensor product polynomial splines
(1997-01-01)
Chen, LA
;
Chan, WY
;
Lee, TS
;
統計學研究所
;
Institute of Statistics
This paper presents a unified study of smoothing tensor product piecewise polynomials as tensor product polynomial splines. This study generalizes the theory of univariate polynomial splines of Poirier (1973) and Smith (1979) to the multivariate setting, and the method proposed herein provides various spline bases that gives great flexibility for selecting models. An example analyzing an Australia wine industry data shows simple tensor product spline can capture the trend in the data appropriately to law of economics whereas multiple lineal model fails in capturing the trend (see Maddala (1988)).