Items where Author is "Ugwoke, P. O."

Article

Okagbue, H. I. and Ijezie, Ogochukwu A. and Ugwoke, P. O. and Adeyemi-Kayode, Temitope M. and Jonathan, Oluranti (2023) Single-label machine learning classification revealed some hidden but inter-related causes of five psychotic disorder diseases. Heliyon, 9. ISSN 2405-8440

Okagbue, H. I. and Opanuga, A. A. and Oguntunde, P.E. and Ugwoke, P. O. (2017) Random number datasets generated from statistical analysis of randomly sampled GSM recharge cards. Data in Brief. pp. 269-276.

Okagbue, H. I. and Adamu, M. O. and Iyase, S.A . and Edeki, S.O. and Opanuga, A. A. and Ugwoke, P. O. (2015) On the Uniqueness and Non-Commutative Nature of Coefficients of Variables and Interactions in Hierarchical Moderated Multiple Regression of Masked Survey Data. Mediterranean Journal of Social Sciences, 6 (4). pp. 408-417. ISSN 2039-2117 (online)2039-9340 (print)

Oguntunde, P.E. and Odetunmibi, , O. A. and Okagbue, H. I. and Babatunde, O. S. and Ugwoke, P. O. (2015) The Kumaraswamy-Power Distribution: A Generalization of the Power Distribution. International Journal of Mathematical Analysis, 9 (13). pp. 637-645.

Conference or Workshop Item

Okagbue, H. I. and Oguntunde, P.E. and Opanuga, A. A. and Ugwoke, P. O. (2018) Classes of Ordinary Differential Equations Obtained for the Probability Functions of Kumaraswamy Kumaraswamy Distribution. In: International MultiConference of Engineers and Computer Scientists 2018 Vol I, March 14-16, 2018, Hong Kong.

Okagbue, H. I. and Agboola, O.O. and Ugwoke, P. O. and Opanuga, A. A. (2017) Classes of Ordinary Differential Equations Obtained for the Probability Function of Exponentiated Pareto Distribution. In: World Congress on Engineering and Computer Science, October 25-27, 2017, San Francisco, USA.

Okagbue, H. I. and Oguntunde, P.E. and Ugwoke, P. O. and Opanuga, A. A. (2017) Classes of Ordinary Differential Equations Obtained for the Probability Functions of Exponentiated Generalized Exponential Distribution. In: World Congress on Engineering and Computer Science, October 25-27, 2017, San Francisco, USA.