Monte Carlo study of a simple model bulk-ice-Ih system:P-Tmelting behavior at constant volume

1992 ◽  
Vol 45 (1) ◽  
pp. 29-35 ◽  
Author(s):  
K. Han ◽  
B. N. Hale
Keyword(s):  
Monte Carlo ◽  
Simple Model ◽  
Monte Carlo Study ◽  
Constant Volume

Monte carlo study of a simple model for micelle structure

1981 ◽  
Vol 79 (3) ◽  
pp. 436-440 ◽  
Author(s):  
Steven W. Haan ◽  
Lawrence R. Pratt
Keyword(s):  
Monte Carlo ◽  
Simple Model ◽  
Monte Carlo Study ◽  
Micelle Structure

Lattice spin simulations of low power photonic liquid-crystal devices

2019 ◽  
Vol 31 (01) ◽  
pp. 2050009
Author(s):  
Rita Asquini ◽  
Antonio d’Alessandro ◽  
Cesare Chiccoli ◽  
Paolo Pasini ◽  
Claudio Zannoni
Keyword(s):  
Monte Carlo ◽  
Liquid Crystal ◽  
Simple Model ◽  
External Field ◽  
Optical Transmission ◽  
Monte Carlo Study ◽  
Photonic Devices ◽  
Slot Waveguide ◽  
Organic Hybrid ◽  
Liquid Crystal Devices

We have performed a detailed Monte Carlo study of photonic devices based on nematic liquid crystal infiltrated in polydimethylsiloxane (PDMS) and in Silicon-Organic Hybrid (SOH) channels, to be used as waveguides. The simulations of a simple model of these slot waveguide shifters have shown the effect of an applied electric external field in two cases with different surface alignments, i.e. planar SOH and homeotropic PDMS. We have investigated the effect of the external field on the optical transmission and the ordering across the cell.

Analyzing Observed Composite Differences Across Groups

Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz
Keyword(s):  
Monte Carlo ◽  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Monte Carlo Study ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Latent Mean Differences ◽  
Partial Invariance ◽  
Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

Detecting Between-Groups Heteroscedasticity in MMR: A Monte Carlo Study

2011 ◽  
Author(s):  
Patrick J. Rosopa ◽  
Amber N. Schroeder ◽  
Jessica Doll
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study
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