Point and interval evaluation of nanoparticles censored sample in the spray process

Document Type : Research Article


1 Department of Mathematics and Statistics, Lahijan branch, Islamic Azad University, Lahijan, Iran

2 Department of Mechanical Engineering, Payame Noor University (PNU), Tehran, Iran


A good nano coating depends on the quality of the collision and spreading behavior of the nanoparticles. Unfortunately, in many cases, nanoparticle spreading data has not been recorded. In this paper, we have extended the evaluation model to predict the unavailable or censored maximum spreading diameter of nanoparticle data. Different point and interval methods have been considered for this problem. Choosing Bayesian evaluation, the Markov Chain Monte Carlo (MCMC) has been proposed as an efficient procedure for estimating the predictive inference for future observation. An important implication of the present study is that the censored maximum diameter data can be predicted well using the proposed methods. Results showed the proposed point predictions are close to real data, the predictive intervals contain the real values, and it verifies the applicability of the prediction techniques for real problems.

Graphical Abstract

Point and interval evaluation of nanoparticles censored sample in the spray process


  • Evaluation of the maximum spreading diameter of nanoparticle data on hydrophobic surface was studied.
  • The generalized inverted exponential model was proposed as an appropriate model.
  • The Markov Chain Monte Carlo procedure and likelihood approach were used to predict the censored data.


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