The truncated g-and-h distribution: estimation and application to loss modeling

2022 ◽  
Author(s):  
Marco Bee
Keyword(s):  
Distribution Estimation ◽  
Loss Modeling

Probability distribution estimation for Web service QoS based on max entropy principle

2013 ◽  
Vol 32 (10) ◽  
pp. 2728-2731
Author(s):  
Zhi-hua DAI ◽  
Xiao-dong FU ◽  
Yuan HUANG ◽  
Nan JIA
Keyword(s):  
Probability Distribution ◽  
Web Service ◽  
Distribution Estimation ◽  
Entropy Principle

scholarly journals Identifying snow in photovoltaic monitoring data for improved snow loss modeling and snow detection

Solar Energy ◽  
2021 ◽  
Vol 223 ◽  
pp. 238-247
Author(s):  
Mari B. Øgaard ◽  
Bjørn L. Aarseth ◽  
Åsmund F. Skomedal ◽  
Heine N. Riise ◽  
Sabrina Sartori ◽  
...  
Keyword(s):  
Monitoring Data ◽  
Loss Modeling

scholarly journals Weed Density and Distribution Estimation for Precision Agriculture Using Semi-Supervised Learning

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 27971-27986
Author(s):  
Shantam Shorewala ◽  
Armaan Ashfaque ◽  
R. Sidharth ◽  
Ujjwal Verma
Keyword(s):  
Supervised Learning ◽  
Precision Agriculture ◽  
Weed Density ◽  
Distribution Estimation

scholarly journals Asymptotic normality of conditional distribution estimation in the single index model

2017 ◽  
Vol 9 (1) ◽  
pp. 162-175
Author(s):  
Diaa Eddine Hamdaoui ◽  
Amina Angelika Bouchentouf ◽  
Abbes Rabhi ◽  
Toufik Guendouzi
Keyword(s):  
Distribution Function ◽  
Confidence Interval ◽  
Asymptotic Normality ◽  
Conditional Distribution ◽  
Conditional Distribution Function ◽  
Single Index ◽  
Index Model ◽  
Single Index Model ◽  
Distribution Estimation

AbstractThis paper deals with the estimation of conditional distribution function based on the single-index model. The asymptotic normality of the conditional distribution estimator is established. Moreover, as an application, the asymptotic (1 − γ) confidence interval of the conditional distribution function is given for 0 < γ < 1.

scholarly journals Adaptive Probability Distribution Estimation Based upon Maximum Entropy

1984 ◽  
Vol R-33 (4) ◽  
pp. 353-357 ◽  
Author(s):  
James E. Miller ◽  
Richard W. Kulp ◽  
George E. Orr
Keyword(s):  
Probability Distribution ◽  
Maximum Entropy ◽  
Distribution Estimation
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