scholarly journals Preface to “A discrete-time interpretation of the Planck-Einstein equation”

2006 ◽  
Vol 2006 ◽  
pp. 1-1
Author(s):  
Vladimir Gontar
Keyword(s):  
Einstein Equation ◽  
Discrete Time ◽  
Physical Meaning ◽  
Space Dynamics

The article titled “A discrete-time interpretation of the Planck-Einstein equation” by A. Boyarsky intends to stimulate open discussions about the physical meaning of discretetime space dynamics. All your comments on this article are most welcome.

scholarly journals A discrete-time interpretation of the Planck-Einstein equation

2006 ◽  
Vol 2006 ◽  
pp. 1-5
Author(s):  
A. Boyarsky
Keyword(s):  
String Theory ◽  
Quantum Gravity ◽  
Einstein Equation ◽  
Discrete Time ◽  
Loop Quantum Gravity ◽  
Empty Space ◽  
Important Conclusion ◽  
Age Of The Universe ◽  
The Times ◽  
The Universe

An important conclusion of both string theory and loop quantum gravity theory is that space and time are ultimately discrete. A consequence of discrete space is that there is empty space between the basic elements of space. Analogously, there are empty times between the times where time exists. When time does not exist, it is meaningless to consider the existence of the universe. In this note we consider a discrete-time interpretation of the Planck-Einstein equation and draw a curious conclusion about the real age of the universe.

The Effect of Partly Missing Covariates on Statistical Power in Randomized Controlled Trials With Discrete-Time Survival Endpoints

Methodology ◽  
2017 ◽  
Vol 13 (2) ◽  
pp. 41-60
Author(s):  
Shahab Jolani ◽  
Maryam Safarkhani
Keyword(s):  
Randomized Controlled Trials ◽  
Discrete Time ◽  
Treatment Effect ◽  
Survival Data ◽  
Controlled Trials ◽  
Missing Covariates ◽  
Indicator Method ◽  
Imputation Methods ◽  
Randomized Controlled ◽  
Baseline Covariates

Abstract. In randomized controlled trials (RCTs), a common strategy to increase power to detect a treatment effect is adjustment for baseline covariates. However, adjustment with partly missing covariates, where complete cases are only used, is inefficient. We consider different alternatives in trials with discrete-time survival data, where subjects are measured in discrete-time intervals while they may experience an event at any point in time. The results of a Monte Carlo simulation study, as well as a case study of randomized trials in smokers with attention deficit hyperactivity disorder (ADHD), indicated that single and multiple imputation methods outperform the other methods and increase precision in estimating the treatment effect. Missing indicator method, which uses a dummy variable in the statistical model to indicate whether the value for that variable is missing and sets the same value to all missing values, is comparable to imputation methods. Nevertheless, the power level to detect the treatment effect based on missing indicator method is marginally lower than the imputation methods, particularly when the missingness depends on the outcome. In conclusion, it appears that imputation of partly missing (baseline) covariates should be preferred in the analysis of discrete-time survival data.

Discrete-Time Delay Dynamics of Boundedly Rational Monopoly

2012 ◽  
Author(s):  
Akio Matsumato ◽  
Ferenc Szidarovsky
Keyword(s):  
Time Delay ◽  
Discrete Time ◽  
Discrete Time Delay

DECOMPOSITION OF NONLINEAR DISCRETE-TIME STOCHASTIC SYSTEMS

1985 ◽  
Vol 5 (4) ◽  
pp. 399-413
Author(s):  
Chongzhao Han
Keyword(s):  
Discrete Time ◽  
Stochastic Systems
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