Selected Projects

Ling, M.H., Balakrishnan, N., Yu, C., and So, H.Y., Inference for One-Shot Devices with Dependent k-Out-of-M Structured Components under Gamma Frailty, Mathematics, vol. 9(23), 3032, 2021.

Balakrishnan, N., Ling, M.H., and So, H.Y., Accelerated Life Testing of One-shot Devices: Data Collection and Analysis, Hoboken, NJ: John Wiley, 2021.

Chan, P.S., So, H.Y., Ng, H.K.T., and Gao, W., Optimal Allocation for Extreme Value Regression Under Time Censoring. In: Computational and Methodological Statistics and Biostatistics , pp.291–307, Springer, Cham, Switzerland,2020.

Balakrishnan, N., So, H.Y., and Ling, M.H., EM algorithm for oneshot device testing with competing risks under Weibull distribution, IEEE Transactions on Reliability, vol. 65(2), pp. 973-991, 2016.

Balakrishnan, N., So, H.Y., and Ling, M.H., A Bayesian approach for one-shot device testing with exponential lifetimes under competing risks, IEEE Transactions on Reliability, vol. 65(1), pp. 469-485, 2016.

Ling, M.H., So, H.Y., and Balakrishnan, N., Likelihood inference under proportional hazards model for one-shot device testing, IEEE Transactions on Reliability, vol. 65(1), pp. 446-458, 2016.

Balakrishnan, N., Ling, M.H., and So, H.Y. Constant-stress accelerated life-test models and data analysis for one-shot devices. In: Principles of Performance and Reliability Modeling and Evaluation: Essays in Honor of Kishor Trivedi on his 70th Birthday, pp.77-108, Springer International Publishing, Switzerland, 2016.

Chan, P.S., Balakrishnan, N., So, H.Y., and Ng, H.K.T., Optimal sample size allocation for multi-level stress testing with exponential regression under type I censoring, Communications in Statistics-Theory and Methods, vol. 45(6), pp. 1831-1852, 2016.

Balakrishnan, N., So, H.Y., and Ling, M.H., EM algorithm for oneshot device testing with competing risks under exponential distribution, Reliability Engineering & System Safety, vol. 137, pp. 129-140, 2015.

Balakrishnan, N., Feng, T. , and So, H.Y., Proportional Odds COMPoisson Cure Rate Model with Gamma Frailty and Associated Inference and Application. In: Trends in Mathematical, Information and Data Sciences. Studies in Systems, Decision and Control, vol 445. Springer, Cham, 2022.

Ling, M.H., So, H.Y., and Balakrishnan, N., A Bayesian Approach for the Analysis of Tumorigenicity Data from Sacrificial Experiments Under Weibull Lifetimes. In: Bayesian Inference and Computation in Reliability and Survival Analysis. Emerging Topics in Statistics and Biostatistics Springer, Cham, Switzerland, pp. 215-237, 2022.

Javed, A., Ma, J., Anderson, L., Mayhew, A., So, H.Y., Griffith, L., Gilsing, A. and Raina, p., Age-appropriate BMI cut-points for cardiometabolic health risk: a cross-sectional analysis of the Canadian Longitudinal Study on Aging, International Journal of Obesity, vol. 46, pp. 1027–1035, 2022.

Rochow, N., Fusch, G., Ali, A., Bhatia, A., So, H.Y., Iskander, R., Chessell, L., el Helou, S., and Fusch C., Individualised target fortification of breast milk with protein, carbohydrates, and fat for preterm infants: a double-blind randomised controlled trial, Clinical Nutrition, vol. 12(2), 288, 2020.

Hamatschek, C., Yousuf, E., Mollers, L.S., So, H.Y., Morrison, K., Fusch, C., and Rochow N., Fat and fat-free mass of preterm and term infants from birth to 6 months: A review of current evidence, Nutrients, vol. 40(1), pp. 54-63, 2020.

O’Hoski,S., Bean J.F., Ma, J., So, H.Y., Kuspinar, A., Richardson, J., Wald, J., and Beauchamp M.K., Physical function and frailty for predicting adverse outcomes in older primary care patients, the Archives of Physical Medicine and Rehabilitation, vol. 101(4), pp. 592-598, 2020.

Rochow, N., Landau-Crangle, E., So, H.Y., Pelc, A., Fusch, G., D¨abritz, .J, G¨opel, W., and Fusch, C., Z-score differences based on cross-sectional growth charts do not reflect the growth rate of very low birth weight infants, PLoS ONE, vol. 14(5), e0216048, 2019.

Rochow, N., AlSamnan, M., So, H.Y., Olbertz, D., Pelc, A., D¨abritz, J., Hentshel, R., Wittwer-Backofen, U., and Voigt, M., Maternal body height is a stronger predictor of birth weight than ethnicity: analysis of birth weight percentile charts, Journal of Perinatal Medicine, vol. 47(1), pp. 22-29, 2018.

Fusch, G., Mitra, S., Topp, H., Agarwal, A., So, H.Y., Bruhs, J., Rochow N., Lange A., Heckmann M., and Fusch C., Source and quality of enteral nutrition influences oxidative stress in preterm infants: a prospective cohort study, Journal of Parenteral & Enteral Nutrition, vol. 42(8), pp. 1288-1294, 2018.

Landau-Crangle, E., Rochow, N., Fenton, T., Liu, K., Ali, A., So, H. Y., Fusch, G., Marrin, M., and Fusch, C., Individualized postnatal growth trajectories for preterm infants, Journal of Parenteral and Enteral Nutrition, vol. 42(6), pp. 1084-1092, 2018. 2

So, H.Y., Thompson, M.E., and Wu, C., COrrelated and Misclassified Binary Observations in Complex Surveys, Canadian Journal of Statistics, vol. 48(4), pp. 633-654, 2020.

Zhu , X., Balakrishnan, N. and So, H.Y., Exact One- and TwoSample Likelihood Ratio Tests based on Time-Constrained Life-Tests from Exponential Distributions, Methodology and Computing in Applied Probability, 2022.

Balakrishnan, N., So, H.Y., and X. J. Zhu, On Box–Muller Transformation and Simulation of Normal Record Data, Communications in Statistics - Simulation and Computation, vol. 45(10), pp. 3670–3682, 2016.

Balakrishnan, N., and So, H.Y., A generalization of quantile-based skew logistic distribution of van Staden and King, Statistics & Probability Letters, vol. 107, pp. 44-51, 2015.