The data are 32 observations on faults in rolls of fabric
A data frame with 32 observations on the following 3 variables.
the length of the roll : a numeric vector
the number of faults in the roll of fabric : a discrete vector
the log of the length of the roll : a numeric vector
The data are 32 observations on faults in rolls of fabric taken from Hinde (1982) who used the EM algorithm to fit a Poisson-normal model. The response variable is the number of faults in the roll of fabric and the explanatory variable is the log of the length of the roll.
This data set and help file is an identical copy
fabric data in package gamlss.data.
Hinde, J. (1982) Compound Poisson regression models: in GLIM 82, Proceedings of the International Conference on Generalized Linear Models, ed. Gilchrist, R., 109–121, Springer: New York.
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