The zero truncated model is usually used in modeling

\r\ncount data without zero. It is the opposite of zero inflated model.

\r\nZero truncated Poisson and zero truncated negative binomial models

\r\nare discussed and used by some researchers in analyzing the

\r\nabundance of rare species and hospital stay. Zero truncated models

\r\nare used as the base in developing hurdle models. In this study, we

\r\ndeveloped a new model, the zero truncated strict arcsine model,

\r\nwhich can be used as an alternative model in modeling count data

\r\nwithout zero and with extra variation. Two simulated and one real

\r\nlife data sets are used and fitted into this developed model. The

\r\nresults show that the model provides a good fit to the data. Maximum

\r\nlikelihood estimation method is used in estimating the parameters.<\/p>\r\n","references":null,"publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 79, 2013"}