Aaron Childs
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Associate Professor Coordinator (Level 1)
HH 213
(905) 525 9140 ext. 23426
(905) 522-0935

Research Area: Probability & Statistics

Research Profile: Statistical Inference, order statistics, outliers
I am interested in the diverse applications of order statistics to statistical inference and outlier accomodation. Some of my research involves order statistics from independent and non-identically distributed (I.NI.D) random variables. I.NI.D. random variables are a generalization of the multiple-outlier slippage model, and therefore have applications to outlier accomodation. Order statistics also have applications in classical inference problems; for example I have developed some hypothesis tests based on order statistics and inverse sampling which provide a more efficient alternative to the standard chi-square test for homogeneity. I have also developed a set of Maple programs that allow one to compute series approximations for moments of order statistics. Another area of interest to me is waiting time problems. My contribution to this area has been to develop new methods, some of which are based on uniform random variables and generating functions, which enable one to solve a wide variety of very complex waiting time problems. I have also been involved in some consulting projects, one of which requires testing for independence between virus and respiratory disease data using time series analysis.

Statistical inference, order statistics, outliers

Math 1B03
Math 1ZA3
Stas 2B03 (Term 1) (Term 2)
Stats 3J04/3Y03

Math 1B03
Math 1ZA3
Stats 2B03 (Term 1) (Term 2)
Stats 3J04/3Y03

Math 1A03
Math 1M03
Stats 2B03

Math 1A03
Math 1M03
Stats 2B03
Stats 6K03

Math 1AA3/1ZB3
Stats 2B03 (I & II Term)
Stats 4A03

Childs, A. (2012). Unification of Dirichlet methodology, Communications in Statistics – Theory and Methods, 41, 1647-1662

Childs, A., Balakrishnan, N., and Chandrasekar, B. (2012). Exact distribution of the MLEs of the parameters and of the quantiles of two-parameter exponential distribution under hybrid censoring, Statistics 46, 441-458.

Childs, A. and Chen, Y. (2011). Multilevel fixed and sequential acceptance sampling: The R package MFSAS, Journal of Statistical Software 43, 1-20.

Childs, A. (2010). Vector extensions of the Dirichlet HC and HD functions, with applications to the sharing problem, Methodology and Computing in Applied Probability 12, 91-109.

Childs, A. (2007). More general, further unified, yet more accessible sharing problem results, The Mathematical Scientist 32, 41-50.

Sobel, M., and Childs, A. (2002). Dirichlet-related probability problems and new tools for solving them, Communications in Statistics – Theory and Methods 31, 2027-2050.

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