scholarly journals Distribution of Myosin Attachment Times Predicted from Viscoelastic Mechanics of Striated Muscle

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
Bradley M. Palmer ◽  
Yuan Wang ◽  
Mark S. Miller
Keyword(s):  
Exponential Distribution ◽  
Gamma Distribution ◽  
Shape Parameter ◽  
Striated Muscle ◽  
Scale Parameter ◽  
Viscoelastic Model ◽  
A Value ◽  
Temporal Events ◽  
Single Exponential

We demonstrate that viscoelastic mechanics of striated muscle, measured as elastic and viscous moduli, emerge directly from the myosin crossbridge attachment time,tatt, also called time-on. The distribution oftattwas modeled using a gamma distribution with shape parameter,p, and scale parameter,β. At 5 mM MgATP,βwas similar between mouseα-MyHC (16.0±3.7 ms) andβ-MyHC (17.9±2.0 ms), andpwas higher (P<0.05) forβ-MyHC (5.6±0.4no units) compared toα-MyHC (3.2±0.9). At 1 mM MgATP,papproached a value of 10 in both isoforms, butβrose only in theβ-MyHC (34.8±5.8 ms). The estimated meantatt(i.e.,pβproduct) was longer in theβ-MyHC compared toα-MyHC, and became prolonged in both isoforms as MgATP was reduced as expected. The application of our viscoelastic model to these isoforms and varying MgATP conditions suggest thattattis better modeled as a gamma distribution due to its representing multiple temporal events occurring withintattcompared to a single exponential distribution which assumes only one temporal event withintatt.

scholarly journals Bayesian Approach in Estimation of Shape Parameter of an Exponential Inverse Exponential Distribution

2020 ◽  
pp. 13-27
Author(s):  
Bashiru Omeiza Sule ◽  
Taiwo Mobolaji Adegoke
Keyword(s):  
Exponential Distribution ◽  
Gamma Distribution ◽  
Loss Function ◽  
Posterior Distribution ◽  
Prior Distribution ◽  
Shape Parameter ◽  
Real Life ◽  
Loss Functions ◽  
Jeffreys Prior ◽  
True Parameter

Aims: This study aimed to obtain the shape parameter of an Exponential Inverted Exponential distribution using different prior distributions under different loss functions. Methodology: The Bayes’ theorem was adopted to obtain the posterior distribution of the shape parameter of an Exponential inverted Exponential distribution for both non-information prior (such as Jeffreys prior, Hartigen prior and Uniform prior) and an informative prior (such as Gamma distribution and chi-square distribution). Different loss functions (such as Entropy loss function, Square error loss function, Al-Bayyati’s loss function and Precautionary loss function) were employed to obtain the estimate parameter of the shape parameter with an assumption that the scale parameter is known. Results: The posterior distribution of the shape parameter of an Exponential Inverted Exponential distribution follows a Gamma distribution for all the prior distribution in the study. Also the Bayes estimate for the simulated datasets and real life dataset were obtained. Conclusion: The Bayes’ estimates for different prior distribution under different loss functions are close to the true parameter value of the shape parameter. The estimators are then compared in terms of their Mean Square Error (MSE) which is computed using R programming language. We deduce that the MSE reduces as the sample size (n) increases.

scholarly journals Time to failure assessment of products at service conditions from accelerated lifetime tests with stress-dependent spread in life

2007 ◽  
Vol 27 (2) ◽  
pp. 209-233 ◽  
Author(s):  
Enrique López Droguett ◽  
Ali Mosleh
Keyword(s):  
Comparative Analysis ◽  
Shape Parameter ◽  
Scale Parameter ◽  
Time To Failure ◽  
Failure Assessment ◽  
Accelerated Lifetime ◽  
Lifetime Testing ◽  
Service Conditions ◽  
Stress Dependent ◽  
Parameter Dependency

In accelerated lifetime testing (ALT) the assumption of stress-independent spread in life is commonly used and accepted because the resulting models are typically easier to use and data or past experience suggest that such a constrain is sometimes valid. However in many situations and with a variety of products the spread in life does depend on stress, i.e., the failure mechanism is not the same for all stress levels. In this paper the assessment of product time to failure at service conditions from ALT with stress-dependent spread is addressed by formulating a Bayesian framework where the time to failure follows a Weibull distribution, scale parameter dependency on stress is given by the Power Law, and two cases for the dependency between shape parameter and stress are discussed: linear relationship and, in order to allow a comparative analysis, stress-independent shape parameter. A previously published dataset is used to illustrate the procedure.

scholarly journals On double stage minimax-shrinkage estimator for generalized Rayleigh model

2016 ◽  
Vol 5 (1) ◽  
pp. 39 ◽  
Author(s):  
Abbas Najim Salman ◽  
Maymona Ameen
Keyword(s):  
Sample Size ◽  
Shape Parameter ◽  
Mean Squared Error ◽  
Scale Parameter ◽  
Rayleigh Distribution ◽  
Shrinkage Estimator ◽  
Squared Error ◽  
Expected Sample Size ◽  
Generalized Rayleigh Distribution ◽  
The Mean

<p>This paper is concerned with minimax shrinkage estimator using double stage shrinkage technique for lowering the mean squared error, intended for estimate the shape parameter (a) of Generalized Rayleigh distribution in a region (R) around available prior knowledge (a<sub>0</sub>) about the actual value (a) as initial estimate in case when the scale parameter (l) is known .</p><p>In situation where the experimentations are time consuming or very costly, a double stage procedure can be used to reduce the expected sample size needed to obtain the estimator.</p><p>The proposed estimator is shown to have smaller mean squared error for certain choice of the shrinkage weight factor y(<strong>×</strong>) and suitable region R.</p><p>Expressions for Bias, Mean squared error (MSE), Expected sample size [E (n/a, R)], Expected sample size proportion [E(n/a,R)/n], probability for avoiding the second sample and percentage of overall sample saved  for the proposed estimator are derived.</p><p>Numerical results and conclusions for the expressions mentioned above were displayed when the consider estimator are testimator of level of significanceD.</p><p>Comparisons with the minimax estimator and with the most recent studies were made to shown the effectiveness of the proposed estimator.</p>

scholarly journals Sequential Estimation of the Scale Parameter of an Exponential Distribution under Bounded Risk Constraint

2017 ◽  
Vol 11 (1) ◽  
pp. 133-148
Author(s):  
Eisa Mahmoudi ◽  
Reyhaneh Lalehzari ◽  
Ghahraman Roughani ◽  
◽  
◽  
...  
Keyword(s):  
Exponential Distribution ◽  
Scale Parameter ◽  
Sequential Estimation ◽  
Bounded Risk ◽  
Risk Constraint
Sign in / Sign up

Export Citation Format

Share Document