scholarly journals A distribution-free, Bayesian goodness-of-fit method for assessing similar scientific prediction equations

2022 ◽  
Vol 107 ◽  
pp. 102638
Author(s):  
Richard A. Chechile ◽  
Daniel H. Barch
2015 ◽  
Vol 43 (2) ◽  
pp. 878-902 ◽  
Author(s):  
Sami Umut Can ◽  
John H. J. Einmahl ◽  
Estate V. Khmaladze ◽  
Roger J. A. Laeven

1983 ◽  
Vol 13 (1) ◽  
pp. 85-88 ◽  
Author(s):  
Susan N. Little

The three-parameter Weibull function met specified standards for goodness of fit as a model for the diameter distributions of mixed stands of western hemlock and Douglas-fir. Weibull distributions estimated by maximum likelihood (MLE) fit 80 of 83 observed diameter distributions at the α = 0.20 level of significance by the Kolmogorov–Smirnov test. Weibull parameter prediction equations were developed by regressing characteristics of 42 stands against MLE of the parameters. The Weibull diameter distributions predicted from stand age, mean diameter, mean height, and trees per acre (1 a = 100 m2) fit 39 of 41 observed distributions in the test group at the α = 0.20 level of significance. These results compared favorably with those found for various forest types by other authors. These prediction equations will prove useful in stand modeling and in updating forest inventories.


Bernoulli ◽  
2020 ◽  
Vol 26 (4) ◽  
pp. 3163-3190
Author(s):  
Sami Umut Can ◽  
John H.J. Einmahl ◽  
Roger J.A. Laeven

1962 ◽  
Author(s):  
Z. W. Birnbaum ◽  
Victor Kuang-Tao Tang

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