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Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probability 1 p a random variable with the Poisson distribution is observed. For instance, when manufacturing equipment is properly aligned, defects might be almost impossible. But when it is misaligned, defects might happen according to a Poisson distribution. Both probability p of the perfect zero defect state and the mean number of defects λ in the imperfect state might depend on covariates. The parameters in this type of models can be estimated using maximum likelihood estimation.
Least significant difference test is an approach to comparing a set of means which controls the family wise error rate at some specific level, let's assume it to be α. The hypothe
Consider a decision faced by a cattle breeder. The breeder must decide how many cattle he should sell in the market each year and how many he should retain for breeding purposes. S
This is given by common network e.g. Phone Company. The public networks are those networks, which are given by common carriers. It can be a telephone company or an other organizati
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Likelihood is the probability of a set of observations provided the value of some parameter or the set of parameters. For instance, the likelihood of the random sample of n observ
The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the mult
Conjugate prior : The distribution for samples from the particular probability distribution such that the posterior distribution at each stage of the sampling is of the identical f
Johnson-Neyman technique: The technique which can be used in the situations where analysis of the covariance is not valid because of the heterogeneity of slopes. With this method
Categorizing continuous variables : A practice which involves the conversion of the continuous variables into the series of the categories, which is common in the field of medical
The regression analysis is used to fit a model describing the relationship of a dependent variable with independent variable(s). Here we have fitted three regression models:
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