Monte Carlo simulation and phase behavior of nonadditive hard-core mixtures in two dimensions

2002 ◽  
Vol 117 (12) ◽  
pp. 5780-5784 ◽  
Author(s):  
F. Saija ◽  
P. V. Giaquinta
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Phase Behavior ◽  
Hard Core ◽  
Two Dimensions

scholarly journals Bias Corrections for Probit and Logit Models with Two-way Fixed Effects

2017 ◽  
Vol 17 (3) ◽  
pp. 517-545 ◽  
Author(s):  
Mario Cruz-Gonzalez ◽  
Iván Fernández-Val ◽  
Martin Weidner
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Panel Data ◽  
Fixed Effects ◽  
Two Dimensions ◽  
Panel Data Models ◽  
Logit Models ◽  
Unobserved Effects ◽  
Parameter Problem ◽  
Bias Corrections

In this article, we present the user-written commands probitfe and logitfe, which fit probit and logit panel-data models with individual and time unobserved effects. Fixed-effects panel-data methods that estimate the unobserved effects can be severely biased because of the incidental parameter problem (Neyman and Scott, 1948, Econometrica 16: 1–32). We tackle this problem using the analytical and jackknife bias corrections derived in Fernández-Val and Weidner (2016, Journal of Econometrics 192: 291–312) for panels where the two dimensions ( N and T) are moderately large. We illustrate the commands with an empirical application to international trade and a Monte Carlo simulation calibrated to this application.

Monte Carlo Simulation of the Phase Behavior of Model Dendrimers

2006 ◽  
Vol 39 (18) ◽  
pp. 6298-6305 ◽  
Author(s):  
Anastassia N. Rissanou ◽  
Ioannis G. Economou ◽  
Athanassios Z. Panagiotopoulos
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Phase Behavior

scholarly journals Phase Behavior Under a Noncentrosymmetric Interaction: Shifted-Charge Colloids Investigated by Monte Carlo Simulation

2014 ◽  
Vol 118 (24) ◽  
pp. 6963-6971
Author(s):  
Luis E. Sánchez-Díaz ◽  
Chwen-Yang Shew ◽  
Xin Li ◽  
Bin Wu ◽  
Gregory S. Smith ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Phase Behavior

Probability Methods for Detecting Randomness in Small Sample Spatial Distributions

1994 ◽  
Vol 78 (3) ◽  
pp. 715-720 ◽  
Author(s):  
Frank O'brien
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Statistical Methods ◽  
Two Dimensions ◽  
Small Sample ◽  
Spatial Distributions ◽  
Theoretical Assumptions ◽  
Simulation Results ◽  
Probability Methods ◽  
Spatial Randomness

Several probability and statistical methods are discussed for detecting spatial randomness in two dimensions. One method is derived and proposed for its ease of application. Monte Carlo simulation results are presented in support of the theoretical assumptions of the proposed method.

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