1. Birnbaum, Z. W., ‎and‎ Saunders, S. C. (1969), A New Family of Life Distributions, Journal of Applied Probability, ‎6 (2), 319-327.‎‎

3. Chang, S. T. and Lu, K. P. (2016), Change-Point Detection for Shifts in Control Charts Using EM Change-Point Algorithms, Quality and Reliability Engineering International, ‎32, 889-900.‎‎

5. Chang, S. T, Lu, K. P. and Yang, M. S. (2015), Fuzzy Change-Point Algorithms for Regression Models, IEEE Transactions on Fuzzy Systems, ‎23 (6), 2343-2357.‎‎

7. Chen, C. W. S., Chan, J. S., Gerlach K. R., and Hsieh, W. Y. L. (2011), A Comparison of Estimators for Regression Models with Change Points, Statistics and Computing, ‎21, 395-414.

9. Ciuperca, G. (2009), The M-Estimation in a Multi-Phase Random Nonlinear ‎Model,‎ Statistics & Probability Letters, ‎75, 573-580.

11. Ciuperca, G. (2011), A General Criterion to Determine the Number of Change-Points, Statistics & Probability Letters, ‎81, 1267-1275.

13. Ciuperca, G. (2004), Maximum Likelihood Estimator in a Two-Phase Nonlinear Regression Model, Statistics & Decisions, ‎22, 335-34‎9.‎

15. Ciuperca, G. and Dapzol, N. (2008), Maximum Likelihood Estimator in a Multi-Phase Random Regression Model, Statistics, ‎42, 363-381

17. Dempster, A. P., Laird N. M., and Rubin D. B. (1977), Maximum Likelihood From Incomplete

18. Data via the EM-Algorithm, Journal of the Royal Statistical Society. Series B (methodological), ‎39, 1-38.‎

20. Fearnhead, P. (2006), Exact and Efficient Bayesian Inference for Multiple Change-Point Problems, Statistics and Computing, ‎16, 203-213.

22. Jafari, F. and Golalizadeh, M. (2024), Double Penalized Mixed Effects Quantile Regression Modeling Using the Maximum Likelihood Approach, Journal of Statistical Sciences, 17(2), 389-405.

24. Jalili, M., Bashiri, M., Manteghi, M. and Tofigh, A. A. (2017). Development of a Piecemeal Regression-Based Approach for Monitoring Multiple Linear Profiles with Phase Interactions. Journal of Quality Engineering and Management, 6(4), 237-249.

26. Julious, S. A. ‎(2001).‎ Inference and Estimation in a Change Point Regression Problem, Journal of the Royal Statistical Society Series D, ‎‎‎‎50, 51-61.‎‎

28. Karl, T.R., Knight, R.W. and Baker, B. (2000), The Record Breaking Global Temperatures of 1997 and 1998‎:‎ Evidence for an Increase in the Rate of Global Warming?, Geophysical Research Letters, ‎27 (5), 719-722 ‎

30. Keshavarz, M. and Huang, B. (2014a),‎ Bayesian and Expectation Maximization Methods for Multivariate Change-Point Detection, Computers & Chemical Engineering, ‎60, 339-353.

32. Keshavarz M. and Huang, B. (2014b)‎,‎‎ Expectation Maximization Method for Multivariate Change-Point Detection in Presence of Unknown and Changing Covariance, Computers & Chemical Engineering, ‎69, 128-146.

34. Loschi, R. H., Pontel, J. G. ‎and‎ Cruz F. R. B. (2010), Multiple Change-Point Analysis for Linear Regression models, Chilean Journal of Statistics, ‎1, 93-112.‎‎

36. Lu, K. P., and Chang, S. T. (2021), Robust Algorithms for Change-Point Regressions Using the t-Distribution, Mathematics, 9, 2394.

38. Menne, J. M. (2005), Abrupt Global Temperature Change and the Instrumental Record, In: Record, 18th Conference on Climate Variability and Change.

40. Muggeo, V. M. ‎R.‎ (2008), Segmented: an R package to Fit Regression Models with Broken-Line Relationships, R News, ‎8, 20-25. ‎

42. von Ottenbreit, M., and De Bin, R. (2024), Automatic Piecewise Linear regression, Computational Statistics, 1-41.‎

44. ‎Yang,‎ F. (2014)‎, Robust Mean Change-Point Detecting Through Laplace Linear Regression Using EM Algorithm, Journal of Applied Mathematics, 2014 (1): 856350.

46. Yildirim S., Singh S.S., and Doucet A. (2014), An Online Expectation-Maximization Algorithm for Change-Point Models, Journal of Computational and Graphical Statistics, ‎22(4), 906-26‎.