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Furthermore, the uncertain hypothesis test and an algorithm for data modification which aimed to find outliers and modify data are studied, then the forecast value and confidence interval be formulated. Finally, a real-life numerical example of applying the above theories be given, this example shows that the uncertain MLE has better performance compare with the uncertain least squares and the least absolute deviations methods. Consequently, the uncertain MLE is a better way to deal with the real-life data.<\/jats:p>","DOI":"10.3233\/jifs-231512","type":"journal-article","created":{"date-parts":[[2023,5,26]],"date-time":"2023-05-26T13:23:01Z","timestamp":1685107381000},"page":"2157-2165","source":"Crossref","is-referenced-by-count":0,"title":["Uncertain maximum likelihood estimation for uncertain Von Bertalanffy regression model with real-life data"],"prefix":"10.1177","volume":"45","author":[{"given":"Hao","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Mathematics and Systems Science, Xinjiang University, Urumqi, PR China"}]},{"given":"Yuhong","family":"Sheng","sequence":"additional","affiliation":[{"name":"College of Mathematics and Systems Science, Xinjiang University, Urumqi, PR China"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-231512_ref1","doi-asserted-by":"crossref","first-page":"246","DOI":"10.2307\/2841583","article-title":"Regression towards mediocrity in 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