[1]. Mallet, J.L. (2002). Geomodeling. Oxford University Press.
[2]. Thornton, J.M., Mariethoz, G., and Brunner, P. (2018). A 3D geological model of a structurally complex Alpine region as a basis for interdisciplinary research. Scientific data. 5 (1): 1-20.
[3]. Sides, E.J. (1997). Geological modelling of mineral deposits for prediction in mining. Geologische Rundschau, 86(2), 342-353.
[4]. Cowan, E.J., R.K. Beatson, H.J. Ross, W.R. Fright, T.J. McLennan, T.R. Evans, J.C. Car. (2003). "Practical implicit geological modelling." In Fifth international mining geology conference, pp. 17-19. Australian Institute of Mining and Metallurgy Bendigo, Victoria, 2003.
[5]. Turner, A.K. (2006). Challenges and trends for geological modelling and visualization. Bulletin of Engineering Geology and the Environment. 65 (2): 109-127.
[6]. Shepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM national conference (pp. 517-524).
[7]. Journel, A.G. (1983). Nonparametric estimation of spatial distributions. Journal of the International Association for Mathematical Geology. 15 (3): 445-468.
[8]. Broomhead, D.S. and Lowe, D. (1988). Radial basis functions, multi-variable functional interpolation and adaptive networks. Royal Signals and Radar Establishment Malvern (United Kingdom).
[9]. Deutsch, C.V. and Journel, A.G. (1998). GSLib. Geostatistical software library and user’s guide, 369.
[10]. Madani, N., Maleki, M., and Sepidbar, F. (2021). Integration of dual border effects in resource estimation: A cokriging practice on a copper porphyry deposit. Minerals. 11 (7): 660.
[11]. Marinoni, O. (2003). Improving geological models using a combined ordinary–indicator kriging approach. Engineering geology. 69 (1-2): 37-45.
[12]. Babak, O. (2014). Inverse distance interpolation for facies modeling. Stochastic environmental research and risk assessment. 28 (6): 1373-1382.
[13]. Yasrebi, A.B., Afzal, P., Wetherelt, A., Foster, P., Madani, N., and Javadi, A. (2016). Application of an inverse distance weighted anisotropic method (IDWAM) to estimate elemental distribution in Eastern Kahang Cu-Mo porphyry deposit, Central Iran. International Journal of Mining and Mineral Engineering. 7 (4): 340-362.
[14]. Yasrebi, A.B., Hezarkhani, A., Afzal, P., and Madani, N. (2019). Application of an Inverse Distance Weighted Anisotropic Method for Rock Quality Designation distribution in Eastern Kahang deposit, Central Iran. Journal of Mining and Metallurgy A: Mining. 55 (1): 1-15.
[15]. Pyrcz, M.J. and Deutsch, C.V. (2014). Geostatistical reservoir modeling. Oxford university press.
[16] Goovaerts, P. (1997). Geostatistics for natural resources evaluation. Oxford University Press on Demand.
[17]. Armstrong, M., Galli, A., Beucher, H., Loc'h, G., Renard, D., Doligez, B., and Geffroy, F. (2011). Plurigaussian simulations in geosciences. Springer Science & Business Media.
[18]. Madani N. (2021) Plurigaussian Simulations. In: Daya Sagar B., Cheng Q., McKinley J., Agterberg F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham.
https://doi.org/10.1007/978-3-030-26050-7_251-1
[19]. Shahbeik, S., Afzal, P., Moarefvand, P., and Qumarsy, M. (2014). Comparison between ordinary kriging (OK) and inverse distance weighted (IDW) based on estimation error. Case study: Dardevey iron ore deposit, NE Iran. Arabian Journal of Geosciences. 7 (9): 3693-3704.
[20]. Rossi, M.E. and Deutsch, C.V. (2013). Mineral resource estimation. Springer Science & Business Media.
[21]. Maleki, M. and Emery, X. (2020). Geostatistics in the presence of geological boundaries: Exploratory tools for contact analysis. Ore Geology Reviews, 120, 103397.
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