On the Exponentiated Weighted Exponential Distribution and Its Basic Statistical Properties

We explore a generalization of the Weighted Exponential (WE) distribution using the exponentiated class/family of distributions. The proposed model is named Exponentiated Weighted Exponential distribution and it serves as an alternative to both the Weighted Exponential distribution and the Exponential distribution. Some of the basic statistical properties of the proposed model are studied and provided. The method of maximum likelihood estimation (MLE) was proposed in estimating the parameters of the mode

A Comparison between Maximum Likelihood and Bayesian Estimation Methods for a Shape Parameter of the Weibull-Exponential Distribution

We considered the Bayesian analysis of a shape parameter of the Weibull-Exponential distribution in this paper. We assumed a class of non-informative priors in deriving the corresponding posterior distributions. In particular, the Bayes estimators and associated risks were calculated under three different loss functions. The performance of the Bayes estimators was evaluated and compared to the method of maximum likelihood under a comprehensive simulation study. It was discovered that for the said parameters to be estimated, the quadratic loss function under both uniform and Jeffrey’s priors should be used for decreasing parameter values while the use of precautionary loss function can be preferred for increasing parameter values irrespective of the variations in sample size

Analysis of selected crime data in Nigeria

Crime isanactthatbringsaboutoffencesanditispunishable under thelaw.MajorcrimesinNigeriaincluderape,kidnapping, murder,burglary,fraud,terrorism,robbery,cyber-crimes,bribery and corruption,moneylaunderingandsoon.Accordingtothe statistics releasedbytheNigerianNationalBureauofStatisticsin 2016,Lagos,Abuja,Delta,Kano,Plateau,Ondo,Oyo,Bauchi,Ada- mawaandGombeStatesmadethetoptenlistofstateswithhigh number ofcrimes.Crimeisanimportanttopicanditisofinterest to usbecauseoftheconsequencesandpenaltiesitattracts(which rangesfrom fine todeath).Thisdataarticlecontainsthepartial analysis(bothdescriptiveandinferential)ofcrimedataset obtained between1999and2013.Theaimofthestudyistoshow the patternandrateofcrimeinNigeriabasedonthedatacollected and toshowtherelationshipsthatexistamongthevariouscrime types. Analyzingthisdatasetcanprovideinsightoncrimeactiv- ities withinNigeri

The Generalized Inverted Generalized Exponential Distribution with an Application to a Censored Data

We propose a two parameter Inverted Generalized Exponential (IGE) and a three parameter Generalized Inverted Generalized Exponential (GIGE) probability models as generalizations of the one-parameter Exponential distribution and some other distributions in the literature. We explore the statistical properties of the GIGE distribution and its parameters were estimated for both censored and uncensored cases using the method of maximum likelihood estimation (MLE). An application to a real data set is also provided to assess the flexibility of the GIGE distribution over some of its sub-models

A Note on the Minimax Distribution

We introduce a one parameter probability model bounded on (0, 1) support called One Parameter Minimax distribution which is a special case of both the Kumaraswamy distribution and Beta distribution. Its statistical properties are systematically explored; we provide explicit expressions for its moments, quantile function, reliability function and failure rate. The method of maximum likelihood estimation was used in estimating its parameter. The proposed model can be used to model data sets with increasing failure rate

The Transmuted Inverse Exponential Distribution

This article introduces a two-parameter probability model which represents another generalization of the Inverse Exponential distribution by using the quadratic rank transmuted map. The proposed model is named Transmuted Inverse Exponential (TIE) distribution and its statistical properties are systematically studied. We provide explicit expressions for its moments, moment generating function, quantile function, reliability function and hazard function. We estimate the parameters of the TIE distribution using the method of maximum likelihood estimation (MLE). The hazard function of the model has an inverted bathtub shape and we propose the usefulness of the TIE distribution in modeling breast cancer and bladder cancer data sets

Theoretical Analysis of the Kumaraswamy-Inverse Exponential Distribution

The Kumaraswamy distribution being a viable alternative to the beta distribution is being used to propose a three-parameter Kumaraswamy-Inverse Exponential distribution and some of its statistical properties are identified

Optimization of Production Plan of Hebron Drinks using Operational Research Technique

Manufacturing companies frequently face challenging operational problems. In such business environment, operations that compete for the same resources must be planned in a way that deadlines are met. Certain expertise in optimization is often required for successful solution of these problems. In this paper, we attempted to optimize the production plan of a manufacturing company - Hebron Drinks, by minimizing the Labour hours, Marching hours and Materials used in producing six different types of products. Linear programming technique was use to model the production plan of Hebron Drinks. The resulted model was solved using simplex method with the aid of computer software (LIP Solver 1.11.1 and 1.11.0). The optimal value obtained shows a reduction in the total cost of production for the period considered

Assessing the Flexibility of the Exponentiated Generalized Exponential Distribution

A three parameter probability model which serves as a generalization of the Exponential distribution was studied. The new model is named Exponentiated Generalized Exponential (EGE) distribution. The shape of the model could be increasing, decreasing or unimodal (depending on the value of the parameters). Explicit expressions are provided for the moments and generating functions, reliability function and failure rate. The method of maximum likelihood estimation (MLE) was proposed for the estimation of the parameters. An application to two real data sets was provided in order to assess the flexibility of the proposed model over some models in the literature