Hurdle negative binomial regression model with right censored count data
MetadataShow full item record
A Poisson model typically is assumed for count data. In many cases because of many zeros in the response variable, the mean is not equal to the variance value of the dependent variable. Therefore, the Poisson model is no longer suitable for this kind of data. Thus, we suggest using a hurdle negative binomial regression model to overcome the problem of overdispersion. Furthermore, the response variable in such cases is censored for some values. In this paper, a censored hurdle negative binomial regression model is introduced on count data with many zeros. The estimation of regression parameters using maximum likelihood is discussed and the goodness-of-fit for the regression model is examined.
Showing items related by title, author, creator and subject.
Chow, Chi Ngok (2010)The largest wool exporter in the world is Australia, where wool being a major export is worth over AUD $2 billion per year and constitutes about 17 per cent of all agricultural exports. Most Australian wool is sold by ...
Jiang, Zhenyu (2011)Genomics is a major scientific revolution in this century. High-throughput genomic data provides an opportunity for identifying genes and SNPs (singlenucleotide polymorphism) that are related to various clinical phenotypes. ...
Chan, Kit Yan; Ling, S.; Dillon, Tharam; Kwong, C. (2011)Fuzzy regression is a commonly used approach for modeling manufacturing processes in which the availability of experimental data is limited. Fuzzy regression can address fuzzy nature of experimental data in which fuzziness ...