Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Olusoga A Fasoranbaku"'
Publikováno v:
Tanzania Journal of Science. 47:1303-1309
This research extends design optimization to model involving count data. A two-variable Poisson regression model was investigated for A-optimality on a constrained design space and the weights of the optimal design points were obtained. The construct
Publikováno v:
Tanzania Journal of Science. 47:999-1006
In the context of generalized linear models, most of the recent studies were on logistic regression models and many of them focussed on optimal experimental designs with concentration on D-optimality. In this research, two- and three-variable Poisson
Publikováno v:
Tanzania Journal of Science. 47:988-998
Bayesian estimations have the advantages of taking into account the uncertainty of all parameter estimates which allows virtually the use of vague priors. This study focused on determining the quantile range at which optimal hyperparameter of normall
Autor:
Olusoga Akin Fasoranbaku, Nurudeen A. Adegoke, Olusola Temitope Omolofe, Olatunde A. Adeoti, Saddam Akber Abbasi
Multivariate control charts are generally used in industries for monitoring and diagnosing processes characterized by several process variables. The applications of charts assume that the in-control process parameters are known and the charts’ limi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b131ae837a443b684363080108dceae
Publikováno v:
Journal of Applied Statistics. 45:1106-1117
In this paper, we consider the notions of data depth for ordering multivariate data and propose a classification rule based on the distribution of some depth functions in Rd. The equivalence of the proposed classification rule to optimal Bayes rule i
Publikováno v:
Journal of Modern Applied Statistical Methods. 10:718-729
Publikováno v:
Global Journal of Mathematical Sciences; Vol 3, No 1 (2004); 11-21
This paper deals with estimation and testing for cointegration when deterministic trends are present in the data generating process. The study confirmed that to estimate the Vector Error Correction Model (VECM) when there is no cointegration will pro