1 |
Andrieu, C., Freitas, N., Doucet, A., and Jordan, M., An Introduction to MCMC for Machine Learning, Machine Learning, 2003, Vol. 50, No. 1, pp. 5-43.
DOI
|
2 |
Bollerslev, T., Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 1986, Vol. 31, No. 3, pp. 307-327.
DOI
|
3 |
Chalupka, K., Williams, C., and Murray, I., A Framework for Evaluating Approximation Methods for Gaussian Process Regression, Journal of Machine Learning Research, 2013, Vol. 14, No. 1, pp. 333-350.
|
4 |
Engle, R., Autoregressive Conditional Hetero scedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, 1982, Vol. 50, No. 4, pp. 987-1007.
DOI
|
5 |
Golub, G. and Van Loan, C., Matrix Computations, The John Hopkins University Press, third edition, 1996.
|
6 |
Han, D. and Kim, J., Implementation of the Real-time Fault Detection and Diagnosis System of Air Handling Unit. Proceedings of the SAREK 2002 Summer Annual Conference, 2002, pp. 301-306.
|
7 |
Han, D. and Youn, H., Building Energy Control Algorithms by Using Outdoor Air Temperature Prediction, Proceedings of the SAREK 2002 Summer Annual Conference, 2002, pp. 345-350.
|
8 |
Kim, J. and Kim, T., Screening and Clustering for timecourse Yeast Microarray Gene Expression Data using Gaussian Process Regression, The Korean Journal of Applied Statistics, 2013, Vol. 26, No. 3, pp. 389-399.
DOI
|
9 |
Lee, P., Bayesian Statistics : An Introduction, 4th Edition, John Wiley and Sons, Chichester, 2012.
|
10 |
Lim, S., Cho, S., and Lee, C., Model for the Spatial Time Series Data, Journal of the Korean Society for Quality Management, 1996, Vol. 24, No. 1, pp. 137-145.
|
11 |
Mills, T., Time Series Techniques for Economists, Cambridge University Press, New York, 1990.
|
12 |
Rasmussen, C. and Williams, C., Gaussian Processes for Machine Learning, the MIT Press, Cambridge, Massachusetts 2006, ch. 5.
|
13 |
Suh, J., Lee, S., Oh. H., Koo, J., Lim, T., and Cho, J., ARMA-PL : Tackling Nested Periods and Linear Trend in Time Series Data, Journal of the Society of Korea Industrial and Systems Engineering, 2010, Vol. 33, pp. 112-126.
|
14 |
Vijayakumar, S., D'Souza, A., Shibata, T., Conradt, J., and Schaal, S., Statistical Learning for Humanoid Robots, Autonomous Robot, 2002, Vol. 12, No. 1, pp. 55-69.
DOI
|
15 |
Sundararajan, S. and Keerthi, S., Predictive Approaches for Choosing Hyperparameters in Gaussian Processes, Neural Computation, 2001, Vol. 13, No. 5, pp. 1103-1118.
DOI
|