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Applied Mathematics-A Journal of Chinese Universities  2018, Vol. 33 Issue (2): 163-    DOI: 10.1007/s11766-018-3354-x
    
Inference for a truncated positive normal distribution
Hector J. Gomez$^1$ , Neveka M. Olmos$^2$,  Hector Varela$^2$ ,  Heleno Bolfarine$^3$
$^1$ Departamento de Ciencias Matem\'aticas y F\'isicas, Facultad de Ingenier\'ia, Universidad Cat\'olica de Temuco, Temuco, Chile.\\
$^2$ Departamento de Matem\'aticas, Facultad de Ciencias B\'asicas, Universidad de Antofagasta, Antofagasta, Chile.\\
$^3$ Departamento de Estat\'istica, IME, Universidade de S\~ao Paulo, S\~ao Paulo, Brazil.
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Abstract  The main  object of this paper is to study an extension of the half normal distribution defined by adding a positive truncation to it. The new model is more flexible than the half-normal distribution  and contains the half normal distribution as a special case. Properties of this distribution, such as moments, hazard function and entropy are studied and parameters estimation is dealt with by using  moments and maximum likelihood. A real data application indicates good fit performance of the new model  when compared to other competitors in literatures.

Key wordshalf-normal distribution              maximum likelihood        truncation     
Published: 02 July 2018
CLC:  62E15  
  62F10  
Cite this article:

Hector J. Gomez, Neveka M. Olmos, Hector Varela, Heleno Bolfarine. Inference for a truncated positive normal distribution. Applied Mathematics-A Journal of Chinese Universities, 2018, 33(2): 163-.

URL:

http://www.zjujournals.com/amjcub/10.1007/s11766-018-3354-x     OR     http://www.zjujournals.com/amjcub/Y2018/V33/I2/163


Inference for a truncated positive normal distribution

The main  object of this paper is to study an extension of the half normal distribution defined by adding a positive truncation to it. The new model is more flexible than the half-normal distribution  and contains the half normal distribution as a special case. Properties of this distribution, such as moments, hazard function and entropy are studied and parameters estimation is dealt with by using  moments and maximum likelihood. A real data application indicates good fit performance of the new model  when compared to other competitors in literatures.

关键词: half-normal distribution ,   ,  maximum likelihood ,   truncation 
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