Justine .N. Mbukwa
BLOCK B (FUNDIKIRA), ROOM No.205
|Postal Address:||Po Box ...., Morogoro Tanzania.|
|BSc. (Applied Statistics)||
Mzumbe University -Tanzania
|M.A (Statistics)||University of Dar es Salaam -Tanzania|
|PhD Candidate (Statistics)||
Acharya Nagarjuna University-India
Applied Multivariate Statistical Modeling, Pattern Recognition and Predictive modeling
Area of Research
- Research interest lies Classification problem and Predictive modeling in crop sciences, business, health sciences, behavioral sciences etc.
- Application of Multivariate Statistical Methodology for high-dimensional and complex data, dimensionality reduction of the covariates, latent factor models, and nonparametric approaches to all fields of natural science, engineering, business studies as well as social sciences.
- An application of Machine learning algorithms (data mining) to model both labeled and unlabeled data to enhance the rational decision making in all fields of studies.
Mbukwa, J. N., Tabita, G. N., Anjaneyulu, G. V. S. R., and Rajasekharam, O. V.(2016). Statistical Analytic Tool for Dimensionalities in Big Data: The role of Hierarchical Cluster Analysis. International Journal of Statistics and Systems, 11(1), pp.19-26.
Mbukwa, J.N.,and Anjaneyulu, G.V.S.R. (2016). Application of k-Means and Partitioning Around Mediods (PAM) Clustering Techniques on Maize and Beans Yield in Tanzania, Bulletin of Math.& Stat.Res, Vol(4), Issue (4), pp.146-158.
Mbukwa, J.N.,and Anjaneyulu, G.V.S.R. (2016). On the use of Sparse Principal Component Analysis and Robust: Selection Features of Maize Yield in Rural Tanzania. Journal of Engineering Mathematics and Statistics, Volume (1), Issue (1), pp.1-26.