Strongly Convergent Homogeneous Approximations to Inhomogeneous Markov Jump Processes and Applications

Published Online:https://doi.org/10.1287/moor.2022.0153

References

  • [1] Albrecher H, Bladt M (2019) Inhomogeneous phase-type distributions and heavy tails. J. Appl. Probab. 56(4):1044–1064.CrossrefGoogle Scholar
  • [2] Albrecher H, Bladt M, Yslas J (2022) Fitting inhomogeneous phase-type distributions to data: The univariate and the multivariate case. Scand. J. Statist. 49(1):44–77.CrossrefGoogle Scholar
  • [3] Arns M, Buchholz P, Panchenko A (2010) On the numerical analysis of inhomogeneous continuous-time Markov chains. INFORMS J. Comput. 22(3):416–432.LinkGoogle Scholar
  • [4] Asmussen S (2003) Applied Probability and Queues, vol. 2 (Springer, New York).Google Scholar
  • [5] Asmussen S, Albrecher H (2010) Ruin Probabilities, vol. 14 (World Scientific, Singapore).CrossrefGoogle Scholar
  • [6] Asmussen S, Nerman O, Olsson M (1996) Fitting phase-type distributions via the EM algorithm. Scand. J. Statist. 23(4):419–441.Google Scholar
  • [7] Assaf D, Langberg NA, Savits TH, Shaked M (1984) Multivariate phase-type distributions. Oper. Res. 32(3):688–702.LinkGoogle Scholar
  • [8] Bladt M (2023) A tractable class of multivariate phase-type distributions for loss modeling. N. Amer. Actuar. J. 27(4):1–21.CrossrefGoogle Scholar
  • [9] Bladt M, Nielsen BF (2010) Multivariate matrix-exponential distributions. Stochastic Models 26(1):1–26.CrossrefGoogle Scholar
  • [10] Bladt M, Nielsen BF (2017) Matrix-Exponential Distributions in Applied Probability, vol. 81 (Springer, New York).CrossrefGoogle Scholar
  • [11] Bladt M, Yslas J (2023) matrixdist: Statistics for matrix distributions. R package version 1.1.7, https://github.com/martinbladt/matrixdist_1.0.Google Scholar
  • [12] Bladt M, Asmussen S, Steffensen M (2020) Matrix representations of life insurance payments. Eur. Actuar. J. 10(1):29–67.CrossrefGoogle Scholar
  • [13] Bladt M, Gonzalez A, Lauritzen SL (2003) The estimation of phase-type related functionals using Markov chain Monte Carlo methods. Scand. Actuar. J. 2003(4):280–300.CrossrefGoogle Scholar
  • [14] Bladt M, Nielsen BF, Samorodnitsky G (2015) Calculation of ruin probabilities for a dense class of heavy tailed distributions. Scand. Actuar. J. 2015(7):573–591.CrossrefGoogle Scholar
  • [15] Breuer L (2016) A semi-explicit density function for Kulkarni’s bivariate phase-type distribution. Stochastic Models 32(4):632–642.CrossrefGoogle Scholar
  • [16] Choudhury G, Mandelbaum A, Reiman M, Whitt W (1997) Fluid and diffusion limits for queues in slowly changing environments. Stochastic Models 13(1):121–146.CrossrefGoogle Scholar
  • [17] Cloth L, Jongerden MR, Haverkort BR (2007) Computing battery lifetime distributions. 37th Annual IEEE/IFIP Internat. Conf. Dependable Systems Networks (DSN’07) (IEEE, Piscataway, NJ), 780–789.Google Scholar
  • [18] Cramer H (1955) Collective Risk Theory (Skandia ins. Company, Stockholm).Google Scholar
  • [19] Csörgo M, Révész P (2014) Strong Approximations in Probability and Statistics (Academic Press, New York).Google Scholar
  • [20] Dollard JD, Friedman CN (1984) Product Integration with Applications to Differential Equations. Encyclopedia of Mathematics and its Applications (Cambridge University Press, Cambridge, MA), xxiii–xxiv.CrossrefGoogle Scholar
  • [21] Fraser DF (1973) The rate of convergence of a random walk to Brownian motion. Ann. Probab. 1(4):699–701.CrossrefGoogle Scholar
  • [22] Frees EW, Valdez EA (1998) Understanding relationships using copulas. N. Amer. Actuar. J. 2(1):1–25.CrossrefGoogle Scholar
  • [23] Frenkel ALI (2009) Non-homogeneous Markov reward model for aging multi-state system under minimal repair. Internat. J. Perform. Engrg. 5(4):303.Google Scholar
  • [24] Friz PK, Hairer M (2020) A Course on Rough Paths (Springer, Cham, Switzerland).CrossrefGoogle Scholar
  • [25] Gill RD (1994) Lectures on Survival Analysis. Lectures on Probability Theory (Springer, Berlin, Heidelberg), 115–241.CrossrefGoogle Scholar
  • [26] Gill RD, Johansen S (1987) Product-integrals and counting processes. Department of Mathematical Statistics (R 8707) (University of Copenhagen, Copenhagen).Google Scholar
  • [27] Grassmann WK (1977) Transient solutions in Markovian queueing systems. Comput. Oper. Res. 4(1):47–53.CrossrefGoogle Scholar
  • [28] Haase M (2006) The Functional Calculus for Sectorial Operators (Birkhäuser, Basel), 19–60.Google Scholar
  • [29] Hampshire RC, Harchol-Balter M, Massey WA (2006) Fluid and diffusion limits for transient sojourn times of processor sharing queues with time varying rates. Queueing Systems 53:19–30.CrossrefGoogle Scholar
  • [30] Helton J, Stuckwisch S (1976) Numerical approximation of product integrals. J. Math. Anal. Appl. 56(2):410–437.CrossrefGoogle Scholar
  • [31] Jacod J, Shiryaev A (2013) Limit Theorems for Stochastic Processes, vol. 288 (Springer Science & Business Media, Berlin, Heidelberg).Google Scholar
  • [32] Janssen J, Manca R (2006) Applied Semi-Markov Processes (Springer Science & Business Media, New York).Google Scholar
  • [33] Jensen A (1953) Markoff chains as an aid in the study of Markoff processes. Scand. Actuar. J. 1953:87–91.CrossrefGoogle Scholar
  • [34] Joe H (2014) Dependence Modeling with Copulas (CRC Press, Boca Raton, FL).CrossrefGoogle Scholar
  • [35] Kulkarni VG (1989) A new class of multivariate phase-type distributions. Oper. Res. 37(1):151–158.LinkGoogle Scholar
  • [36] Kurtz TG (1971) Limit theorems for sequences of jump Markov processes approximating ordinary differential processes. J. Appl. Probab. 8(2):344–356.CrossrefGoogle Scholar
  • [37] Lawless JF (2011) Statistical Models and Methods for Lifetime Data (John Wiley & Sons, Hoboken, NJ).Google Scholar
  • [38] Lundberg F (1903) Approximerad framställning av sannolikhetsfunktionen. aterförsäkring av kollektivrisker. Akad. Ph.D. thesis, Almqvist och Wiksell Uppsala, Sweden.Google Scholar
  • [39] Mandelbaum A, Massey WA (1995) Strong approximations for time-dependent queues. Math. Oper. Res. 20(1):33–64.LinkGoogle Scholar
  • [40] Mandelbaum A, Massey WA, Reiman MI (1998) Strong approximations for Markovian service networks. Queueing Systems 30:149–201.CrossrefGoogle Scholar
  • [41] Massey WA (1985) Asymptotic analysis of the time dependent M/M/1 queue. Math. Oper. Res. 10(2):305–327.LinkGoogle Scholar
  • [42] Massey WA, Whitt W (1998) Uniform acceleration expansions for Markov chains with time-varying rates. Ann. Appl. Probab. 8(4):1130–1155.CrossrefGoogle Scholar
  • [43] Moler C, Van Loan C (2003) Nineteen dubious ways to compute the exponential of a matrix, twenty-five years later. SIAM Rev. 45(1):3–49.CrossrefGoogle Scholar
  • [44] Neuts MF (1975) Probability Distributions of Phase-Type (Liber Amicorum Prof. Emeritus H. Florin, Louvain, Belgium).Google Scholar
  • [45] Nguyen GT, Peralta O (2022) Rate of strong convergence to Markov-modulated Brownian motion. J. Appl. Probab. 59(1):1–16.CrossrefGoogle Scholar
  • [46] Prokhorov YV (1956) Convergence of random processes and limit theorems in probability theory. Theory Probab. Appl. 1(2):157–214.CrossrefGoogle Scholar
  • [47] Rindos A, Woolet S, Viniotis I, Trivedi K (1995) Exact Methods for the Transient Analysis of Nonhomogeneous Continuous Time Markov Chains. Computations with Markov Chains (Springer, Boston), 121–133.Google Scholar
  • [48] Shi D, Guo J, Liu L (2005) On the SPH-distribution class. Acta Math. Sci. Ser. B Engl. Ed. 25(2):201–214.CrossrefGoogle Scholar
  • [49] Skorokhod AV (1956) Limit theorems for stochastic processes. Theory Probab. Appl. 1(3):261–290.CrossrefGoogle Scholar
  • [50] Strassen V (1964) An invariance principle for the law of the iterated logarithm. Z. Wahrscheinlichkeitstheor. Verwandte Geb. 3(3):211–226.CrossrefGoogle Scholar
  • [51] Telek M, Horvath A, Horváth G (2004) Analysis of inhomogeneous Markov reward models. Linear Algebra Appl. 386:383–405.CrossrefGoogle Scholar
  • [52] van Dijk NM (1992) Uniformization for nonhomogeneous Markov chains. Oper. Res. Lett. 12(5):283–291.CrossrefGoogle Scholar
  • [53] van Dijk NM, van Brummelen SPJ, Boucherie RJ (2018) Uniformization: Basics, extensions and applications. Perform. Eval. 118:8–32.CrossrefGoogle Scholar
  • [54] van Moorsel AP, Wolter K (1998) Numerical solution of non-homogeneous Markov processes through uniformization. Proc. 12th European Simulation Multiconference – Simulation Past, Present and Future (SCS, Europe), 710–717.Google Scholar
  • [55] Whitt W (2002) Stochastic-process limits: An introduction to stochastic-process limits and their application to queues. Space 500:391–426.Google Scholar
  • [56] Wong E, Zakai M (1965) On the relation between ordinary and stochastic differential equations. Internat. J. Engrg. Sci. 3(2):213–229.CrossrefGoogle Scholar
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