References
- Dai X, Jin L, Tian M. Bayesian local influence for spatial autoregressive models with heteroscedasticity. Stat Pap. 2019;60(5):1423–1446.
- Kargoll B, Dorndorf A, Omidalizarandi M, et al. Adjustment models for multivariate geodetic time series with vector-autoregressive errors. J Appl Geodesy. 2021;15(3):243–267.
- Leiva V, Saulo H, Souza R, et al. A new BISARMA time series model for forecasting mortality using weather and particulate matter data. J Forecast. 2021;40(2):346–364.
- Liu T, Liu S, Shi L. Time series analysis using SAS enterprise guide. Singapore: Springer; 2020.
- Liu Y, Ji G, Liu S. Influence diagnostics in a vector autoregressive model. J Stat Comput Simul. 2015;85(13):2632–2655.
- Liu Y, Sang R, Liu S. Diagnostic analysis for a vector autoregressive model under student-t distributions. Stat Neerl. 2017;71(2):86–114.
- Lütkepohl H. New introduction to multiple time series analysis. Berlin, Germany: Springer; 2005.
- Meintanis SG, Ngatchou-Wandji J, Allison J. Testing for serial independence in vector autoregressive models. Stat Pap. 2018;59(4):1379–1410.
- Nduka UC, Ugah TE, Izunobi CH. Robust estimation using multivariate t innovations for vector autoregressive models via ECM algorithm. J Appl Stat. 2021;48(4):693–711.
- Tsay RS. Multivariate time series analysis: with R and financial applications. New York: Wiley; 2014.
- Atkinson AC, Riani M, Cerioli A. Exploring multivariate data with the forward search. Berlin, Germany: Springer; 2004.
- Cook RD. Assessment of local influence (with discussion). J R Stat Soc B. 1986;48:133–169.
- Li WK. Diagnostic checks in time series. Boca Raton, FL: Chapman & Hall/CRC; 2004.
- Liu S, Leiva V, Zhuang D, et al. Matrix differential calculus with applications in the multivariate linear model and its diagnostics. J Multivar Anal. 2022;188:104849.
- Liu S, Welsh AH. Regression diagnostics. In Lovric M editor. International Encyclopedia of Statistical Science. New York: Springer; 2011. p. 1206–1208.
- Pan JX, Fang KT. Growth curve models and statistical diagnostics. New York: Springer; 2002.
- von Rosen D. Influential observations in multivariate linear models. Scand J Stat. 1995;22: 207–222.
- von Rosen D. Bilinear regression analysis. Cham, Switzerland: Springer; 2018.
- Hao CC, von Rosen D, von Rosen T. Local influence analysis in AB-BA crossover designs. Scand J Stat. 2014;41(4):1153–1166.
- Kim SK, Huggins R. Diagnostics for autocorrelated regression models. Aust N Z J Stat. 1998;40(1):65–71.
- Paula GA. Influence diagnostics for linear models with first-order autoregressive elliptical errors. Stat Probab Lett. 2009;79(3):339–346.
- Shi L, Ojeda M. Local influence in multilevel regression for growth curve. J Multivar Anal. 2004;91(2):282–304.
- Tsai CL, Wu X. Assessing local influence in linear regression models with first-order autoregressive or heteroscedastic error structure. Stat Probab Lett. 1992;14(3):247–252.
- Liu S. On diagnostics in conditionally heteroskedastic time series models under elliptical distributions. J Appl Probab. 2004;41A:393–405.
- Liu S, Heyde CC. On estimation in conditional heteroskedastic time series models under non-normal distributions. Stat Pap. 2008;4(3):455–469.
- Liu S, Neudecker H. On pseudo maximum likelihood estimation for multivariate time series models with conditional heteroskedasticity. Math Comput Simul. 2009;79(8):2556–2565.
- Liu Y, Mao C, Leiva V, et al. Asymmetric autoregressive models: statistical aspects and a financial application under COVID-19 pandemic. J Appl Stat. 2022;49(5):1323–1347.
- Liu Y, Mao G, Leiva V, et al. Diagnostic analytics for an autoregressive model under the skew-normal distribution. Mathematics. 2020;8(5):693.
- Liu Y, Wang J, Yao Z, et al. Diagnostic analytics for a GARCH model under skew-normal distributions. Commun Stat Simul Comput. 2022;1:1–25. doi:10.1080/03610918.2022.2157015
- Lu J, Shi L, Chen F. Outlier detection in time series models using local influence method. Commun Stat: Theory Methods. 2012;41(12):2202–2220.
- Rao CR. Linear statistical inference and its applications. New York: Wiley; 1973.
- Rao CR. Score test: Historical review and recent developments. In Balakrishnan N, Nagaraja HN, Kannan N, editors, Advances in Ranking and Selection, Multiple Comparisons, and Reliability. Boston: Birkhäuser; 2005. p. 3–20.
- Engle RF. Wald, likelihood ratio, and Lagrange multiplier tests in econometrics. In: Intriligator MD and Griliches Z, editors. Handbook of Econometrics. Vol. II, Amsterdam: Elsevier; 1984. p. 775–826.
- Godfrey LG. Misspecification tests in econometrics. Cambridge: Cambridge University Press; 1988.
- Gumedze F, Welham S, Gogel B. A variance shift model for detection of outliers in the linear mixed model. Comput Stat Data Anal. 2010;54(9):2128–2144.
- Jiang D. Tests for large-dimensional covariance structure based on Rao's score test. J Multi Anal. 2016;152:28–39.
- Kirch C, Muhsal B, Ombao H. Detection of changes in multivariate time series with application to EEG data. J Am Stat Assoc. 2015;110(511):1197–1216.
- Kollo T, von Rosen D. Advanced multivariate statistics with matrices. New York: Springer; 2005.
- Magnus JR, Neudecker H. Matrix differential calculus with applications in statistics and econometrics. Chichester: Wiley; 2019.
- Ferguson TS. On the rejection of outliers. In: Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability. Vol. 1, 1961. p. 253–287.