91 research outputs found
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
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