Asymptotically refined score and GOF tests for inverse Gaussian models

References

• Banerjee AK, Bhattacharyya GK. A purchase incidence model with inverse Gaussian interpurchase times. J Amer Statist Assoc. 1976;71:823–829. doi: 10.1080/01621459.1976.10480953
   Web of Science ®Google Scholar
• Chhikara RS, Folks JL. The inverse Gaussian distribution as a lifetime model. Technometrics. 1977;19:461–468. doi: 10.1080/00401706.1977.10489586
   Web of Science ®Google Scholar
• Chhikara RS, Folks JL. The inverse Gaussian distribution and its statistical application - a review. J R Statist Soc B. 1978;40:263–289.
   Google Scholar
• Chhikara RS, Folks JL. The inverse Gaussian distribution: theory, methodology and applications. New York: Marcel Dekker; 1989.
   Google Scholar
• Desmond AF, Chapman GR. Modelling task completion data with inverse Gaussian mixtures. Appl Stat. 1993;42:603–613. doi: 10.2307/2986178
   Web of Science ®Google Scholar
• Desmond AF, Yang ZL. Score tests for inverse Gaussian mixtures. Appl Stoch Models Bus Ind. 2011;27:633–648. doi: 10.1002/asmb.876
   Web of Science ®Google Scholar
• Ducharme GR. Goodness-of-fit tests for the inverse Gaussian and related distributions. Test. 2001;10:271–290. doi: 10.1007/BF02595697
   Web of Science ®Google Scholar
• Edgeman RL. Inverse Gaussian control charts. Aust J Stat. 1989;31:78–84. doi: 10.1111/j.1467-842X.1989.tb00500.x
   Google Scholar
• Edgeman RL. Assessing the inverse Gaussian distribution assumption. IEEE Trans Reliab. 1990;R39:352–355. doi: 10.1109/24.103017
   Web of Science ®Google Scholar
• Johnson NL, Kotz S, Balakrishnan N. Continuous univariate distribution. New York: Wiley; 1994.
   Google Scholar
• Hawkins DM, Olwell DH. Inverse Gaussian cumulative sum control charts for location and shape. The Statistician. 1997;46:323–335.
   Google Scholar
• Lancaster T. A stochastic model for the duration of a strike. J R Statist Soc A. 1972;135:257–271. doi: 10.2307/2344321
   Web of Science ®Google Scholar
• Lee M-LT, Whitmore GA. Threshold regression for survival analysis: Modeling event times by a stochastic process reaching a boundary. Statist Sci. 2006;4:501–513. doi: 10.1214/088342306000000330
   Web of Science ®Google Scholar
• Lee M-LT, Whitmore GA. Proportional hazards and threshold regression: Their theoretical and practical connections. Lifetime Data Anal. 2010;16:196–214. doi: 10.1007/s10985-009-9138-0
   PubMed Web of Science ®Google Scholar
• Pavur RJ, Edgeman RL, Scott RC. Quadratic statistics for the goodness-of-fit test of the inverse Gaussian distribution. IEEE Trans Reliab. 1992;41:118–123. doi: 10.1109/24.126682
   Web of Science ®Google Scholar
• Seshadri V. The inverse Gaussian distribution: a case study in exponential families. Oxford: Oxford University Press; 1993.
   Google Scholar
• Seshadri V. The inverse Gaussian distribution. New York: Springer; 1998.
   Google Scholar
• Whitmore GA. An inverse Gaussian model for labour turnover. J R Statist Soc A. 1979;142:468–478. doi: 10.2307/2982553
   Web of Science ®Google Scholar
• Whitmore GA. Normal-gamma mixtures of inverse Gaussian distribution. Scand J Stat. 1986;13:211–220.
   Web of Science ®Google Scholar
• Letac G, Seshadri V, Whitmore GA. An exact chi-squared decomposition theorem for inverse Gaussian variates. J R Statist Soc B. 1985;47:476–481.
   Google Scholar
• Aalen OO, Borgan O, Gjessing HK. Survival and event history analysis: a process point of view. New York: Springer; 2008.
   Google Scholar
• Feller W. An introduction to probability theory and its applications, Vol. II. New York: Wiley; 1966.
   Google Scholar
• Aalen OO. Effects of frailty in survival analysis. Statist Methods Med Res. 1994;3:227–243. doi: 10.1177/096228029400300303
   PubMedGoogle Scholar
• Cox DR, Hinkley DV. Theoretical statistics. London: Chapman and Hall; 1974.
   Google Scholar
• Rayner JCW, Thas O, Best DJ. Smooth tests of goodness of fit using R. 2nd ed. Singapore: John Wiley & Sons; 2009.
   Google Scholar
• Yang ZL. LM tests of spatial dependence based on bootstrap critical values. J Economet. 2015;185:33–59. doi: 10.1016/j.jeconom.2014.10.005
   Web of Science ®Google Scholar
• Hall P. The bootstrap and edgeworth expansion. New York: Springer; 1992.
   Google Scholar
• Hall P, Horowitz JL. Bootstrap critical values for tests based on generalized-method-of-moments estimators. Econometrica. 1996;64:891–916. doi: 10.2307/2171849
   Web of Science ®Google Scholar
• Lawless JF. Statistical models and methods for lifetime data. 2nd ed. Hoboken, NJ: Wiley; 2003.
   Google Scholar
• Davison AC, Hinkley DV. Bootstrap methods and their applications. London: Cambridge University Press; 1997.
   Google Scholar
• Efron B. Censored data and the bootstrap. J Amer Statist Assoc. 1981;76:312–319. doi: 10.1080/01621459.1981.10477650
   Web of Science ®Google Scholar
• Whitmore GA. A regression method for censored inverse-Gaussian data. Canad J Stat. 1983;11:305–315. doi: 10.2307/3314888
   Google Scholar
• Lemonte AJ, Ferrari SLP. The local power of the gradient test. Ann Instit Statist Math. 2012;64:373–381. doi: 10.1007/s10463-010-0315-4
   Web of Science ®Google Scholar
• Terrell GR. The gradient statistic. Comput Sci Stat. 2002;34:206–215.
   Google Scholar
• Rao CR. Score test: historical review and recent developments. In: Balakrishnan N, Kannan N, Nagaraja HN, editors. Advances in ranking and selection, multiple comparisons, and reliability. Boston, MA: Birkhauser; 2005.
   Google Scholar