Understanding patterns of aggregation in count data

Understanding patterns of aggregation in count data

The term aggregation refers to overdispersion and both are used interchangeably in this thesis. In addressing the problem of prevalence of infectious parasite species faced by most rural livestock farmers, we model the distribution of faecal egg counts of 15 parasite species (13 internal parasites a...

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Bibliographic Details
Main Author: Sebatjane, Phuti
Other Authors: Njuho, Peter
Format: Others
Language:en
Published: 2017
Subjects:
Aggregations
Autoregressive models
Akaike information criterion
Correlation
Count data
Exponential family
Generalised linear models
Goats
Internal parasites
Hosts
Negative binomial distribution
Overdispersion
Poisson distribution
Sheep
Time series
Zero inflation
519.537
Correlation (Statistics)
Akaike Information Criterion
Exponential functions
Livestock > Parasites
Time-series analysis
Binomial distribution
Online Access:Sebatjane, Phuti (2016) Understanding patterns of aggregation in count data, University of South Africa, Pretoria, <http://hdl.handle.net/10500/22067>
http://hdl.handle.net/10500/22067

Internet

Sebatjane, Phuti (2016) Understanding patterns of aggregation in count data, University of South Africa, Pretoria, <http://hdl.handle.net/10500/22067>
http://hdl.handle.net/10500/22067

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