Mean and Variance of Truncated Normal Distributions

1999 ◽  
Vol 53 (4) ◽  
pp. 357-361 ◽  
Author(s):  
Donald R. Barr ◽  
E. Todd Sherrill
Keyword(s):  
Normal Distributions ◽  
Mean And Variance ◽  
Truncated Normal

Mean and Variance of Truncated Normal Distributions

1999 ◽  
Vol 53 (4) ◽  
pp. 357 ◽  
Author(s):  
Donald R. Barr ◽  
E. Todd Sherrill
Keyword(s):  
Normal Distributions ◽  
Mean And Variance ◽  
Truncated Normal

Truncated Normal Distributions

Nature ◽  
1950 ◽  
Vol 165 (4194) ◽  
pp. 444-445 ◽  
Author(s):  
H. R. THOMPSON
Keyword(s):  
Normal Distributions ◽  
Truncated Normal

Letter to the editor: Fitting truncated normal distributions

2017 ◽  
Vol 27 (12) ◽  
pp. 3835-3838
Author(s):  
Iain L MacDonald
Keyword(s):  
Em Algorithm ◽  
Normal Distributions ◽  
Letter To The Editor ◽  
The Em Algorithm ◽  
Truncated Normal

I comment here on a recent paper in this journal, on the fitting of truncated normal distributions by the EM algorithm. I show that the fitting of such distributions by direct numerical maximization of likelihood (rather than EM) is straightforward, contrary to an assertion made by the authors of that paper.

Comparison among Some Methods for Estimating the Parameters of Truncated Normal Distribution

2021 ◽  
Vol 20 ◽  
pp. 79-95
Author(s):  
Hilmi Kittani ◽  
Mohammad Alaesa ◽  
Gharib Gharib
Keyword(s):  
Normal Distribution ◽  
Moment Method ◽  
Truncated Normal Distribution ◽  
Moment Methods ◽  
Distribution Parameters ◽  
Mean And Variance ◽  
Truncated Normal ◽  
The Mean ◽  
Censored Sampling ◽  
Mean Square Errors

The aim of this study is to investigate the effect of different truncation combinations on the estimation of the normal distribution parameters. In addition, is to study methods used to estimate these parameters, including MLE, moments, and L-moment methods. On the other hand, the study discusses methods to estimate the mean and variance of the truncated normal distribution, which includes sampling from normal distribution, sampling from truncated normal distribution and censored sampling from normal distribution. We compare these methods based on the mean square errors, and the amount of bias. It turns out that the MLE method is the best method to estimate the mean and variance in most cases and the L-moment method has a performance in some cases.

Sign in / Sign up

Export Citation Format

Share Document