scholarly journals A Bayesian Estimate of the COVID-19 Infection Fatality Ratio in Brazil Based on a Random Seroprevalence Survey

2021 ◽  
Author(s):  
Valerio Marra ◽  
Miguel Quartin
Keyword(s):  
Bayesian Estimate

Comments on "Two dimensional Bayesian estimate of images"

1976 ◽  
Vol 64 (8) ◽  
pp. 1255-1257 ◽  
Author(s):  
M.G. Strintzis ◽  
A. Habibi
Keyword(s):  
Bayesian Estimate ◽  
Two Dimensional

A Bayesian Estimate of the Pricing Kernel

2016 ◽  
Author(s):  
Chiara Legnazzi ◽  
Giovanni Barone-Adesi ◽  
Antonietta Mira
Keyword(s):  
Bayesian Estimate ◽  
Pricing Kernel

scholarly journals Adjusting An Existing Forecasting Model When Some Future Demands Are Known In Advance: A Bayesian Technique

2011 ◽  
Vol 4 (7) ◽  
Author(s):  
Raida Abuizam ◽  
Nick T. Thomopoulos
Keyword(s):  
Bayesian Estimate ◽  
Forecasting Model ◽  
Expected Number ◽  
Future Period ◽  
Forecasting Error ◽  
Future Demands

The purpose of this research is to provide a model which can be used to adjust forecasts that are already available. It analyzes the components of the advanced demand, namely, the number of orders and their corresponding order size. It explores and analyzes the possibility of using the expected number of orders for a future period as the variable to be estimated. The Bayesian estimate of the expected number of orders is used in determining the adjusted forecast. A simulation is applied to calculate a ratio between the adjusting forecasting error and the original forecasting error. Results prove that the adjusted forecast provides greater accuracy for different probable values of getting an order in advance.

A Bayesian estimate of harbour seal survival using sparse photo-identification data

2007 ◽  
Vol 0 (0) ◽  
pp. 070728062702006-??? ◽  
Author(s):  
B. L. Mackey ◽  
J. W. Durban ◽  
S. J. Middlemas ◽  
P. M. Thompson
Keyword(s):  
Bayesian Estimate ◽  
Harbour Seal ◽  
Photo Identification

A Bayesian Estimate of Vehicle Safety Performance

2005 ◽  
Author(s):  
L. Gu ◽  
G. Li ◽  
J. Abramczyk ◽  
J. Prybylski
Keyword(s):  
Safety Performance ◽  
Bayesian Estimate ◽  
Vehicle Safety

BAYESIAN RELIABILITY APPROACH TO THE POWER LAW PROCESS WITH SENSITIVITY ANALYSIS TO PRIOR SELECTION

2013 ◽  
Vol 20 (01) ◽  
pp. 1350004
Author(s):  
CARLOS A. MOLINARES ◽  
CHRIS P. TSOKOS
Keyword(s):  
Maximum Likelihood ◽  
Power Law ◽  
Real Data ◽  
Random Variable ◽  
Intensity Function ◽  
Rate Of Change ◽  
Bayesian Estimate ◽  
Squared Error Loss Function ◽  
Power Law Process ◽  
Prior Selection

The intensity function is the key entity to the power law process, also known as the Weibull process or nonhomogeneous Poisson process. It gives the rate of change of the reliability of a system as a function of time. We illustrate that a Bayesian analysis is applicable to the power law process through the intensity function. First, we show using real data, that one of the two parameters in the intensity function behaves as a random variable. With a sequence of estimates of the subject parameter we proceeded to identify the probability distribution that characterizes its behavior. Using the commonly used squared-error loss function we obtain a Bayesian reliability estimate of the power law process. Also a simulation procedure shows the superiority of the Bayesian estimate with respect to the maximum likelihood estimate and the better performance of the proposed estimate with respect to its maximum likelihood counterpart. As well, it was found that the Bayesian estimate is sensitive to a prior selection.

Bayesian estimate of pre-mixed and diffusive rate of heat release phases in marine diesel engines

2016 ◽  
Vol 39 (5) ◽  
pp. 1835-1844 ◽  
Author(s):  
Marcelo A. Pasqualette ◽  
Diego C. Estumano ◽  
Fabiana C. Hamilton ◽  
Marcelo J. Colaço ◽  
Albino J. K. Leiroz ◽  
...  
Keyword(s):  
Heat Release ◽  
Diesel Engines ◽  
Bayesian Estimate ◽  
Marine Diesel ◽  
Rate Of Heat Release
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