Industrial resources, Horry County: Conway

This is a 1968 report generated by the Conway Chamber of Commerce and the South Carolina State Development Board to provide potential industrial developers with information about industry in Horry County, particularly Conway, and to promote new development. The report includes detailed statistics and descriptive information about industry in Horry County and in Conway in the form of text statements as well as charts and maps. This information covers, at the county and city levels: county and community services and resources, agricultural resources, communications, labor supply, economics, and education, state, county, and city taxation, utility and transportation availability, weather and climate data, local recreation, and industrial site availability.

The Conway-Maxwell-Poisson-generalized gamma regression model with long-term survivors

In this paper, we proposed a flexible cure rate survival model by assuming the number of competing causes of the event of interest following the Conway-Maxwell distribution and the time for the event to follow the generalized gamma distribution. This distribution can be used to model survival data when the hazard rate function is increasing, decreasing, bathtub and unimodal-shaped including some distributions commonly used in lifetime analysis as particular cases. Some appropriate matrices are derived in order to evaluate local influence on the estimates of the parameters by considering different perturbations, and some global influence measurements are also investigated. Finally, data set from the medical area is analysed.

The zero-inflated Conway-Maxwell-Poisson distribution: Bayesian inference, regression modeling and influence diagnostic

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Bayesian analysis of the Conway-Maxwell-Poisson cure rate model

The purpose of this paper is to develop a Bayesian analysis for the right-censored survival data when immune or cured individuals may be present in the population from which the data is taken. In our approach the number of competing causes of the event of interest follows the Conway-Maxwell-Poisson distribution which generalizes the Poisson distribution. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the proposed model. Also, some discussions on the model selection and an illustration with a real data set are considered.

Elm tree. Conway Valley

[From Jasper Cropsey Sketch book, 1855-1856]