References
- Albert, J. H., & Chib, S. (1993). Bayes inference via Gibbs sampling of autoregressive time series subject to Markov mean and variance shifts. Journal of Business & Economic Statistics, 11(1), 1–15.
- Anand, P. B., Fennell, S., & Comim, F. (2019). Handbook of brics and emerging economies. Oxford University Press.
- Chan, K. S., & Tong, H. (1986). On estimating thresholds in autoregressive models. Journal of Time Series Analysis, 7(3), 179–190. https://doi.org/https://doi.org/10.1111/j.1467-9892.1986.tb00501.x
- Chaturvedi, A., & Kumar, J. (2005). Bayesian unit root test for model with maintained trend. Statistics & Probability Letters, 74(2), 109–115. https://doi.org/https://doi.org/10.1016/j.spl.2005.04.044
- Cockfield, S. D., Fitzpatrick, S. M., Giles, K. V., & Mahr, D. L. (1994). Hatch of black headed fire worm (Lepidoptera: Tortricidae) eggs and prediction with temperature-driven models. Environmental Entomology, 23(1), 101–107. https://doi.org/https://doi.org/10.1093/ee/23.1.101
- Duggal, A. (2017). Foreign direct investment in India. Journal of Internet Banking and Commerce, 22(3), 1–10.
- Huang, J. Z., & Shen, H. (2004). Functional coefficient regression models for non-linear time series: A polynomial spline approach. Scandinavian Journal of Statistics, 31(4), 515–534. https://doi.org/https://doi.org/10.1111/j.1467-9469.2004.00404.x
- Krishnankutty, C. (2001). Teak price trends in Kerala state. India. Indian Journal of Forestry, 24(1), 1–7.
- Kumar, J., Shukla, A., & Tiwari, N. (2014). Bayesian analysis of a stationary AR (1) model and outlier. Electronic Journal of Applied Statistical Analysis, 7(1), 81–93.
- Kyung, M. (2011). A computational Bayesian method for estimating the number of knots in regression splines. Bayesian Analysis, 6(4), 793–828. https://doi.org/https://doi.org/10.1214/11-BA629
- Liu, J. M. (2009). Non-linear time series modeling using spline-based nonparametric models. In Proceedings of the 15th American Conference on Applied Mathematics (pp. 183–189). World Scientific and Engineering Academy and Society (WSEAS).
- Maryam, J., & Mittal, A. (2020). Foreign direct investment into BRICS: An empirical analysis. Transnational Corporations Review, 12(1), 1–9. https://doi.org/https://doi.org/10.1080/19186444.2019.1709400
- Meyer, N., & Meyer, D. (2017). An econometric analysis of entrepreneurial activity, economic growth and employment: The case of the BRICS countries. International Journal of Economic Perspectives, 11(2), 429–441.
- Mohanty, S., & Sethi, N. (2019). Outward FDI, human capital and economic growth in BRICS countries: An empirical insight. Transnational Corporations Review, 11(3), 235–249. https://doi.org/https://doi.org/10.1080/19186444.2019.1657347
- Morton, R., Kang, E. L., & Henderson, B. L. (2009). Smoothing splines for trend estimation and prediction in time series. Environmetrics, 20(3), 249–259. https://doi.org/https://doi.org/10.1002/env.925
- Schotman, P. C., & Van Dijk, H. K. (1991). On Bayesian routes to unit roots. Journal of Applied Econometrics, 6(4), 387–401. https://doi.org/https://doi.org/10.1002/jae.3950060407
- Siddiqui, K. (2016). Will the growth of the BRICs cause a shift in the global balance of economic power in the 21st century? International Journal of Political Economy, 45(4), 315–338. https://doi.org/https://doi.org/10.1080/08911916.2016.1270084
- Wang, H. B., & Wu, P. (2015). Bayesian inference of autoregressive and functional-coefficient moving average models. Communications in Statistics - Theory and Methods, 44(3), 453–467. https://doi.org/https://doi.org/10.1080/03610926.2012.742110
- Yang, Y., & Song, Q. (2014). Jump detection in time series nonparametric regression models: A polynomial spline approach. Annals of the Institute of Statistical Mathematics, 66(2), 325–344. https://doi.org/https://doi.org/10.1007/s10463-013-0411-3