Research on Estimation Methods for the Upper-Truncated Geometric Mixture Distribution

Geometric model is a widely used discrete probabilistic model. The uppper-truncated geometric model which is derived from geometric model also has important applications in real life. In this paper we will specify the upper-truncated geometric mixed model, study its non-parametric and parameter estimation methods. The maximum conditional likelihood estimation of unknown parameters is proposed based on gaussian distribution, beta distribution and gamma distribution. Meanwhile, combined with simulation and an example, the applications of the upper-truncated geometric model is illustrated.