scholarly journals Bayesian Estimation for Two Parameters of Gamma Distribution Under Precautionary Loss Function

2019 ◽  
Vol 32 (1) ◽  
pp. 193 ◽  
Author(s):  
Loaiy F. Naji ◽  
Huda Abdullah Rasheed
Keyword(s):  
Bayesian Estimation ◽  
Gamma Distribution ◽  
Loss Function ◽  
Simulation Method ◽  
Mean Squared Errors ◽  
Scale Parameters ◽  
Lindley’S Approximation ◽  
The Mean ◽  
Two Parameters ◽  
Better Than

In the current study, the researchers have been obtained Bayes estimators for the shape and scale parameters of Gamma distribution under the precautionary loss function, assuming the priors, represented by Gamma and Exponential priors for the shape and scale parameters respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s). The results show that, the performance of Bayes estimator under precautionary loss function with Gamma and Exponential priors is better than other estimates in all cases.

scholarly journals Bayesian Estimation for Two Parameters of Gamma Distribution under Generalized Weighted Loss Function

2019 ◽  
Vol 60 (5) ◽  
pp. 1161-1171
Author(s):  
Loaiy F. Naji ◽  
Huda A. Rasheed
Keyword(s):  
Bayesian Estimation ◽  
Gamma Distribution ◽  
Loss Function ◽  
Maximum Likelihood Estimators ◽  
Simulation Method ◽  
Monte Carlo Simulation Method ◽  
Mean Squared Errors ◽  
Scale Parameters ◽  
The Mean ◽  
Two Parameters

This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

scholarly journals Bayesian Estimation for Two Parameters of Weibull Distribution under Generalized Weighted Loss Function

2021 ◽  
Vol 34 (4) ◽  
pp. 116-129
Author(s):  
Abtisam J. Kadhim ◽  
Huda A. Rasheed
Keyword(s):  
Weibull Distribution ◽  
Bayesian Estimation ◽  
Loss Function ◽  
Simulation Method ◽  
Bayes Estimators ◽  
Mean Squared Errors ◽  
Scale Parameters ◽  
The Mean ◽  
Two Parameters

In this paper, Bayes estimators for the shape and scale parameters of Weibull distribution have been obtained using the generalized weighted loss function, based on Exponential priors. Lindley’s approximation has been used effectively in Bayesian estimation. Based on theMonte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s).

scholarly journals Some Bayes Estimators for Maxwell Distribution by Using New Loss Function

2017 ◽  
Vol 28 (1) ◽  
pp. 103
Author(s):  
Huda A. Rasheed ◽  
Zainab N. Khalifa
Keyword(s):  
Monte Carlo Simulation ◽  
Loss Function ◽  
Scale Parameter ◽  
Simulation Method ◽  
Monte Carlo Simulation Method ◽  
Maxwell Distribution ◽  
Bayes Estimators ◽  
Mean Squared Errors ◽  
The Mean ◽  
Bayesian Estimations

In the current study, we have been derived some Bayesian estimations of the scale parameter of Maxwell distribution using the New loss function (NLF) which it called Generalized weighted loss function, assuming non-informative prior, namely, Jefferys prior and information prior, represented by Inverted Levy prior. Based on Monte Carlo simulation method, those estimations are compared depending on the mean squared errors (MSE's). The results show that, the behavior of Bayesian estimation under New loss function using Inverted Levy prior when (k=0, c=3) is the better behavior than other estimates for all cases.

scholarly journals Variability in rainfall dispersion in Madhya Pradesh

MAUSAM ◽  
2021 ◽  
Vol 43 (1) ◽  
pp. 29-36
Author(s):  
H.P. DAS ◽  
A. CHOWDHURY
Keyword(s):  
Gamma Distribution ◽  
Rainfall Variability ◽  
Probability Model ◽  
Regional Distribution ◽  
Madhya Pradesh ◽  
Regression Equations ◽  
Scale Parameters ◽  
Agronomic Practices ◽  
Distribution Probability ◽  
The Mean

An attempt has been made to examine distribution and dispersion in rainfall variability in Madhya Pradesh by applying Gamma distribution probability model, The spatial and regional distribution of shape and scale parameters of the Gamma distribution have been examined, Periods of water surpluses and deficiencies have been identified by comparing the probability rainfall with the water requirement. Regression equations have been developed to find probabilitistic rainfall from the mean rainfall. Agronomic practices have been evaluated for efficient utilization of water resources for crop planning.  

scholarly journals PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis

2021 ◽  
Vol 9 ◽  
Author(s):  
Shui-Hua Wang ◽  
Ziquan Zhu ◽  
Yu-Dong Zhang
Keyword(s):  
Neural Network ◽  
Infectious Disease ◽  
Convolutional Neural Network ◽  
Loss Function ◽  
Data Augmentation ◽  
State Of The Art ◽  
Diagnosis System ◽  
Backbone Network ◽  
The Mean ◽  
Better Than

Objective: COVID-19 is a sort of infectious disease caused by a new strain of coronavirus. This study aims to develop a more accurate COVID-19 diagnosis system.Methods: First, the n-conv module (nCM) is introduced. Then we built a 12-layer convolutional neural network (12l-CNN) as the backbone network. Afterwards, PatchShuffle was introduced to integrate with 12l-CNN as a regularization term of the loss function. Our model was named PSCNN. Moreover, multiple-way data augmentation and Grad-CAM are employed to avoid overfitting and locating lung lesions.Results: The mean and standard variation values of the seven measures of our model were 95.28 ± 1.03 (sensitivity), 95.78 ± 0.87 (specificity), 95.76 ± 0.86 (precision), 95.53 ± 0.83 (accuracy), 95.52 ± 0.83 (F1 score), 91.7 ± 1.65 (MCC), and 95.52 ± 0.83 (FMI).Conclusion: Our PSCNN is better than 10 state-of-the-art models. Further, we validate the optimal hyperparameters in our model and demonstrate the effectiveness of PatchShuffle.

scholarly journals Multi-label topic classification for COVID-19 literature annotation using an ensemble model based on PubMedBERT

2021 ◽  
Author(s):  
Shubo Tian ◽  
Jinfeng Zhang
Keyword(s):  
Deep Learning ◽  
Loss Function ◽  
Language Model ◽  
Ensemble Model ◽  
Test Results ◽  
Learning Models ◽  
Baseline Model ◽  
Satisfactory Performance ◽  
The Mean ◽  
Better Than

The BioCreative VII Track 5 calls for participants to tackle the multi-label classification task for automated topic annotation of COVID-19 literature. In our participation, we evaluated several deep learning models built on PubMedBERT, a pre-trained language model, with different strategies addressing the challenges of the task. Specifically, multi-instance learning was used to deal with the large variation in the lengths of the articles, and focal loss function was used to address the imbalance in the distribution of different topics. We found that the ensemble model performed the best among all the models we have tested. Test results of our submissions showed that our approach was able to achieve satisfactory performance with an F1 score of 0.9247, which is significantly better than the baseline model (F1 score: 0.8678) and the mean of all the submissions (F1 score: 0.8931).

An Estimator of Normal Covariance Matrix

1980 ◽  
Vol 29 (3-4) ◽  
pp. 161-168 ◽  
Author(s):  
Divakar Sharma
Keyword(s):  
Covariance Matrix ◽  
Loss Function ◽  
Triangular Matrices ◽  
The Mean ◽  
Lower Triangular ◽  
Lower Triangular Matrices ◽  
Mean Vector ◽  
Better Than

Solliah (1964), by considering the group of lower triangular matrices, suggested an estimator of the normal covariance matrix Σ when the mean vector is known and the loss function is tr [Formula: see text] His estimator besides being minimax is better than the MLB of Σ. In this paper, we improve upon his estimator and calculate the reduction in the risk when Σ is 2×2.

scholarly journals The Role of Back Optic Zone Diameter in Myopia Control with Orthokeratology Lenses

2021 ◽  
Vol 10 (2) ◽  
pp. 336
Author(s):  
Jaume Pauné ◽  
Silvia Fonts ◽  
Lina Rodríguez ◽  
Antonio Queirós
Keyword(s):  
Pupillary Diameter ◽  
Myopia Progression ◽  
Zone Diameter ◽  
Power Change ◽  
Ring Diameter ◽  
The Mean ◽  
Two Parameters ◽  
Better Than ◽  
Myopia Control

We compared the efficacy of controlling the annual increase in axial length (AL) in myopic Caucasian children based on two parameters: the back optic zone diameter (BOZD) of the orthokeratology (OK) lens and plus power ring diameter (PPRD) or mid-peripheral annular ring of corneal steepening. Data from 71 myopic patients (mean age, 13.34 ± 1.38 years; range, 10–15 years; 64% male) corrected with different BOZD OK lenses (DRL, Precilens) were collected retrospectively from a Spanish optometric clinic. The sample was divided into groups with BOZDs above or below 5.00 mm and the induced PPRD above or below 4.5 mm, and the relation to AL and refractive progression at 12 months was analyzed. Three subgroups were analyzed, i.e., plus power ring (PPR) inside, outside, or matching the pupil. The mean baseline myopia was −3.11 ± 1.46 D and the AL 24.65 ± 0.88 mm. Significant (p < 0.001) differences were found after 12 months of treatment in the refractive error and AL for the BOZD and PPRD. AL changes in subjects with smaller BOZDs decreased significantly regarding larger diameters (0.09 ± 0.12 and 0.15 ± 0.11 mm, respectively); in subjects with a horizontal sector of PPRD falling inside the pupil, the AL increased less (p = 0.035) than matching or outside the pupil groups by 0.04 ± 0.10 mm, 0.10 ± 0.11 mm, and 0.17 ± 0.12 mm, respectively. This means a 76% lesser AL growth or 0.13 mm/year in absolute reduction. OK corneal parameters can be modified by changing the OK lens designs, which affects myopia progression and AL elongation. Smaller BOZD induces a reduced PPRDs that slows AL elongation better than standard OK lenses. Further investigations should elucidate the effect of pupillary diameter, PPRD, and power change on myopia control.

Photo-electric Hβ and uvby photometry

1966 ◽  
Vol 24 ◽  
pp. 170-180
Author(s):  
D. L. Crawford
Keyword(s):  
Narrow Band ◽  
Line Strength ◽  
Interference Filter ◽  
B Stars ◽  
Relative Line ◽  
The Mean ◽  
F Stars ◽  
Two Parameters ◽  
Filter Photometry ◽  
The Continuum

Early in the 1950's Strömgren (1, 2, 3, 4, 5) introduced medium to narrow-band interference filter photometry at the McDonald Observatory. He used six interference filters to obtain two parameters of astrophysical interest. These parameters he calledlandc, for line and continuum hydrogen absorption. The first measured empirically the absorption line strength of Hβby means of a filter of half width 35Å centered on Hβand compared to the mean of two filters situated in the continuum near Hβ. The second index measured empirically the Balmer discontinuity by means of a filter situated below the Balmer discontinuity and two above it. He showed that these two indices could accurately predict the spectral type and luminosity of both B stars and A and F stars. He later derived (6) an indexmfrom the same filters. This index was a measure of the relative line blanketing near 4100Å compared to two filters above 4500Å. These three indices confirmed earlier work by many people, including Lindblad and Becker. References to this earlier work and to the systems discussed today can be found in Strömgren's article inBasic Astronomical Data(7).

Essai d'application de modèles météorologiques au calcul du moment d'apparition de deux phases phénologiques | Application of Meteorological Models for the Calculation of the Beginning of Two Phenological Phases

2000 ◽  
Vol 151 (10) ◽  
pp. 385-397
Author(s):  
Bernard Primault
Keyword(s):  
Sunshine Duration ◽  
Fruit Trees ◽  
Swiss Alps ◽  
Winter Solstice ◽  
Phenological Data ◽  
Thermal Thresholds ◽  
The Mean ◽  
Two Parameters ◽  
Meteorological Models ◽  
Phenological Phases

Many years ago, a model was elaborated to calculate the«beginning of the vegetation's period», based on temperatures only (7 days with +5 °C temperature or more). The results were correlated with phenological data: the beginning of shoots with regard to spruce and larch. The results were not satisfying, therefore, the value of the two parameters of the first model were modified without changing the second one. The result, however, was again not satisfying. Research then focused on the influence of cumulated temperatures over thermal thresholds. Nevertheless, the results were still not satisfying. The blossoming of fruit trees is influenced by the mean temperature of a given period before the winter solstice. Based on this knowledge, the study evaluated whether forest trees could also be influenced by temperature or sunshine duration of a given period in the rear autumn. The investigation was carried through from the first of January on as well as from the date of snow melt of the following year. In agricultural meteorology, the temperature sums are often interrelated with the sunshine duration, precipitation or both. However,the results were disappointing. All these calculations were made for three stations situated between 570 and 1560 m above sea-level. This allowed to draw curves of variation of the two first parameters (number of days and temperature) separately for each species observed. It was finally possible to specify the thus determined curves with data of three other stations situated between the first ones. This allows to calculate the flushing of the two tree species, if direct phenological observation is lacking. This method, however, is only applicable for the northern part of the Swiss Alps.

Sign in / Sign up

Export Citation Format

Share Document