Publication search results
Matches for:- Author=Peiris MS
2. Shitan M, Peiris MS. Note on the Properties of Generalised Separable Spatial Autoregressive Process, Journal of Probability and Statistics, vol. 2009 (2009), 1–11.
3. Shitan M, Peiris MS. On properties of the second order generalized autoregressive GAR(2) model with index, Mathematics and Computers in Simulation, 80 (2009), no. Issue 2, 367–377.
4. Shitan M, Peiris MS. Generalized Autoregressive (GAR) Model: A Comparison of Maximum Likelihood and Whittle Estimation Procedures Using a Simulation Study,, Communications in Statistics, Simulation and Computation, 37 (2008), 560–570..
5. Thavaneswaran A, Peiris MS, Appadoo S. Random Coefficient Volatility Models, Statistics and Probability Letters, 78 (2008), 582–593. MR2409521
6. Thavaneswaran A, Peiris MS, Singh J. Derivation of Kurtosis and Option Pricing Formulae for Popular Volatility Models with Applications in Finance, Communications in Statistics—Theory and Methods, 37 (2008), no. 1, 1799–1814. MR2431451
7. Perera DI, Peiris MS, Robinson J, Weber NC. The empirical saddlepoint method applied to testing for serial correlation in panel time series data, Statistics and Probability Letters, 78 (2008), 2876–2882.
8. Allen D, Chan F, McAleer M, Peiris MS. Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks, Journal of Econometrics, 147 (2008), 163–185. MR2472990
9. Peiris MS, Thavaneswaran A. An introduction to volatility models with indices, Applied Mathematics Letters, 20 (2007), no. 2, 177–182. MR2283907
10. Bertram WK, Peiris MS. An example of a misclassification problem to Australian equity data, Computational Statistics and Data Analysis, 51 (2007), 3627–3630. MR2364479
11. Peiris MS, Ng KH, Ibrahim IM. A Review of Recent Developments of Financial Time Series: ACD Modelling using the Estimating Function Approach, Sri Lankan Journal of Applied Statistics, 8 (2007), 1–17.
12. Perera DI, Peiris MS, Robinson J, Weber NC. Saddlepoint approximation methods for testing of serial correlation in panel time series data, Journal of Statistical Computation and Simulation, 76 (2006), no. 11, 1001–1015. MR2255899
13. Peiris MS, Allen D, Yang W. Some statistical models for durations and an application to News Corporation stock prices, Mathematics and Computers in Simulation, 68 (2005), 549–556. MR2156401
14. Thavaneswaran A, Appadoo S, Peiris MS. Forecasting volatility, Statistics and Probability Letters, 75 (2005), 1–10. MR2185597
15. Bertram WK, Peiris MS. Increasing the quality of volatility forecasts with fractional ARIMA models, Proceedings of the 2004 Workshop on Research Methods: Statistics and Finance, The 2004 Workshop on Research Methods: Statistics and Finance, Eric J Beh, Robert G Clark, J C W Rayner (eds.), University of Wollongong, Wollongong, (2005), 66–74. ISBN 1 74128 107 5
16. Peiris MS, Allen D, Peiris U. Generalised autoregressive models with conditional heteroscedasticity: An application to financial time series modelling, Proceedings of the 2004 Workshop on Research Methods: Statistics and Finance, The 2004 Workshop on Research Methods: Statistics and Finance, Eric J Beh, Robert G Clark, J C W Rayner (eds.), University of Wollongong, Wollongong, (2005), 75–83. ISBN 1 74128 107 5
17. Allen D, Peiris MS, Yang JW. An examination of the role of time and its impact on price revision, Australian Journal of Management, 30 (2005), no. 2, 283–301.
18. Thavaneswaran A, Peiris MS. Smoothed estimates for models with random coefficients and infinite variance, Mathematical Computation and Modelling, 39 (2004), 363–372. MR2046529
19. Peiris MS, Thavaneswaran A. A note on the filtering for some time series models, Journal of Time Series Analysis, 25 (2004), no. 3, 397–407. MR2063642
20. Peiris MS, Rao CR. A note on testing for serial correlation in large number of small samples using tail probability approximations, Communications in Statistics. Theory and Methods, 33 (2004), no. 8, 1767–1777. MR2065173
21. Peiris MS, Rao CR. An application of Edgeworth expansion on testing for serial correlation in large number of small samples, Sri Lankan Statistical Conference, Visions of Futuristic Methodologies, B. M. de Silva and N. Mukhopadhyay (eds.), PGIS, University of Peradeniya, Peradeniya, Sri Lanka, (2004), 341–354. ISBN 0 86459 339 2
22. Perera DI, Peiris MS. Significance testing for Lag One serial correlation in repeated measurements using saddlepoint approximation, Sri Lankan Statistical Conference, Visions of Futuristic Methodologies, B. M. de Silva and N. Mukhopadhyay (eds.), PGIS, University of Peradeniya, Peradeniya, Sri Lanka, (2004), 363–370. ISBN 0 86459 339 2
23. Peiris MS, Allen D, Thavaneswaran A. An introduction to generalized moving average model and applications, Journal of Applied Statistical Science, 13 (2004), no. 3, 251–267. MR2162151
24. Hunt RL, Peiris MS, Weber NC. The bias of lag window estimators of the fractional difference parameter, Journal of Applied Mathematics and Computing, 12 (2003), 67–79. 2004a:62156
25. Peiris MS, Allen D, Yang W. Some statistical models for durations and their applications in finance, Modsim, International Congress on Modelling and Simulation, 2003, Modelling and Simulation Society of Australia and New Zealand Inc., Australia, (2003), 1210–1214. ISBN 174052 098X
26. Thavaneswaran A, Peiris MS. Generalized smoothed estimating functions for nonlinear time series, Statistics and Probability Letters, 65 (2003), 51–56. MR2012624
27. Peiris MS, Mellor R, Ainkaran P. Maximum likelihood estimation for short time series with replicated observations: a simulation study, InterStat, 9, 11 (2003), no. 3, 1–16.
28. Pemajayantha V, Mellor R, Peiris MS, Rajasekera R. Current Research in Modelling, Data Mining and Quantitative Techniques, University of Western Sydney, University of Western Sydney Press, (2003), 314. ISBN 0-975-1599-0-9
29. Ainkaran P, Peiris MS, Mellor R. A note on the analysis of short AR(1) type time series models with replicated observations, Current Research in Modelling, Data Mining and Quantitative Techniques, University of Western Sydney Press, University of Western Sydney, (2003), 143–156. ISBN 0-975-1599-0-9
30. Perera D, Peiris MS, Weber NC. A Note on the Distribution of Serial Correlation in Large number of Small Samples, Current Research in Modelling, Data Mining and Quantitative Techniques, University of Western Sydney Press, University of Western Sydney, (2003), 172–192. ISBN 0-975-1599-0-9
31. Peiris MS. Improving the quality of forecasting using generalized AR models: an application to statistical quality control, Statistical Methods, 5 (2003), no. 2, 156–171. MR2198741
32. Peiris MS, Thavaneswaran A, Allen D, Mellor R. Applications of recursive estimation methods in statistical process control: a comparison, Statistical Methods, 5 (2003), no. 2, 172–183. MR2198742
33. Singh N, Vadavalli VSS, Peiris MS. A Note on the Modelling and Analysis of Vector ARMA Processes with Nonstationary Innovations, Mathematical and Computer Modelling, 36 (2002), 1409–1424. 2003k:62240
34. Peiris MS. Teaching Mathematical Statistic, Scholarly Inquiry in Flexible ScienceTeaching and Learning, Flexible Science Teaching and Learning, 2002, UniServe Science, Sydney University, (2002), 85–86. ISBN 1 86487 4902
35. Peiris MS. A way of teaching statistics: An approach to flexible learning, CAL-laborate, 9 (2002), 13–15.
36. Thavaneswaran A, Peiris MS. Inference for some time series models with random coefficients and infinite variance, Mathematical and Computer Modelling, 33 (2001), 843–849. MR1826538
37. Peiris MS, Thavaneswaran A. Recursive estimation for regression with infinite variance fractional ARIMA noise, Mathematical and Computer Modelling, 34 (2001), 1133–1137. MR1858841
38. Peiris MS, Thavaneswaran A. Multivariate stable ARMA Processes with time dependent coefficients, Metrika, 54 (2001), no. 2, 131–138. 2002i:62166
39. Peiris MS, Thavaneswaran A. On the properties of some nonstationary ARMA processes with infinite variance, International Journal of Modelling and Simulation, 21 (2001), 301–304.
40. Thavaneswaran A, Peiris MS. Estimation for regression with infinite variance errors, Mathematical and Computer Modelling, 29 (1999), 177–180. MR1704773
41. Thavaneswaran A, Peiris MS. Hypothesis testing for some time-series models: a power comparison, Statistics and Probability Letters, 38 (1998), 151–156. 99e:62166
42. Singh A, Peiris MS. A simulation study on vector arma processes with nonstationary innovation: a new approach to identification, Journal of Statistical Computation and Simulation, 58 (1997), 37–58.
43. Anh V, Lunney K, Peiris MS. Stochastic models for characterisation and prediction of time series with long-range dependence and fractality, Environmental Modelling and Software, 12 (1997), no. 1, 67–73.
44. Abraham B, Thavaneswaran A, Peiris MS. On the prediction scheme for some nonlinear time series models using estimating functions, Selected Proceedings of the Symposium on Estimating Functions, Symposium on Estimating Functions, Ishwar V. Basawa, V.P. Godambe and Robert Taylor (eds.), Lecture Notes - Monograph Series, Institute of Mathematical Statistics, Hayward, California, (1997), 259–271.
45. Poznanski RR, Peiris MS. Subthreshold response to white-noise current input in a tapering cable model of a neuron, IMA Journal of Mathematics Applied In Medicine and Biology, 13 (1996), 207–222.
46. Thavaneswaran A, Peiris MS. Nonparametric estimation for some nonlinear models, Statistics and Probability Letters, 28 (1996), 227–233. 97e:62113
47. Peiris MS. Improving the precision of forecasting, Microelectronics and Reliability, 36 (1996), 1375–1378.
48. Peiris MS, Singh N. Predictors for seasonal and nonseasonal fractionally integrated arima models, Biometrical Journal, 38 (1996), 741–752. 99c:62260
49. Rai SN, Abraham B, Peiris MS. Analysis of Short Time Series with Over-dispersion Model, Communications in Statistics. Theory and Methods, 24 (1995), no. 2, 335–348. MR1345662
50. Peiris MS. Some Aspects of Forecasting with Vector MA Processes, Bulletin of the Calcutta Statistical Association, 44 (1995), 175–176.
51. Chen G, Abraham B, Peiris MS. Lag window estimation of the degree of differencing in fractionally integrated time series models, Journal of Time Series Analysis, 15 (1994), no. 5, 473–487. MR1292162
52. Peiris MS, Court JR. A note on the estimation of the degree of differencing in long memory time series, Journal of Probability and Mathematical Statistics, 14 (1993), no. 2, 223–229. 96b:62145
53. Peiris MS. Some non-stationary ARMA models, Advances in Modelling and Simulation, 27 (1991), 21–34.
54. Peiris MS. Analysis of multivariate ARMA processes with nonstationary innovations, Communications in Statistics. Theory and Methods, 19 (1990), 2847–2852. 92b:62135
55. Peiris MS, Singh N. Optimal experimental design for linear time series models with stochastic coefficients, Journal of the Indian Society for Statistics and Operations Research, 10 (1989), 1–4. MR1201934
56. Peiris MS. On the study of some functions of Multivariate ARMA processes, Journal of Multivariate Analysis, 25 (1988), no. 1, 146–151. 89d:62094
57. Peiris MS, Perera BJC. On the prediction with fractionally differenced ARMA models, Journal of Time Series Analysis, 9 (1988), 215–220. 90a:62250
58. Peiris MS. A note on the predictors of differenced sequences, The Australian Journal of Statistics, 29 (1987), 42–48. 88g:62202
59. Peiris MS, Singh N. A note on the properties of some nonstationary ARMA processes, Stochastic Processes and their Applications, 24 (1987), 151–155. 88g:60099
60. Peiris MS, Singh N. A simple and asymptotically optimal test of equality for q > 2 multivariate normal distributions: A pragmatic approach to one way classification, Microelectronics and Reliability, 27 (1987), 567–573.
61. Peiris MS, Singh N. On prediction of multivariate ARMA processes with a time dependent covariance structure, Communications in Statistics. Theory and Methods, 17 (1987), 27–37. MR0951704
62. Peiris MS, Singh N. Optimal experimental design for linear time series models with stochastic coefficients, Journal of the Indian Society for Statistics and Operations Research, 8 (1987), 1–9. MR0918016
63. Peiris MS. On prediction with time dependent ARMA models, Communications in Statistics. Theory and Methods, 15 (1986), 3659–3668. MR0871332
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