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

On the Exponentiated Generalized Weibull Distribution: A Generalization of the Weibull Distribution

In this article, a generalization of the Weibull distribution is being studied in some details. The new model is referred to as the Exponentiated Generalized Weibull distribution. The aim is to increase the flexibility of the Weibull distribution. Methods: The concepts introduced in the Exponentiated Generalized family of distributions due to Cordeiro et al.11 were employed. Findings: Some basic mathematical properties of the resulting model were identified and studied in minute details. Meanwhile, estimation of model parameters was performed using the maximum likelihood method. Application/Improvement: The Exponentiated Generalized Weibull distribution was presented as a competitive model that would be useful in modeling real life situations with inverted bathtub failure rates. The R-code for the plots was also provided. Further research would involve applying the proposed model to real life data sets