A new Monte Carlo simulation for two models of self-avoiding lattice trees in two dimensions

1985 ◽  
Vol 41 (1-2) ◽  
pp. 95-114 ◽  
Author(s):  
Sergio Caracciolo ◽  
Ueli Glaus
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Two Dimensions ◽  
Lattice Trees

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.

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.

QUASI2D: a program written to demonstrate quasiperiodicity and phason fluctuation

1992 ◽  
Vol 25 (5) ◽  
pp. 648-652
Author(s):  
T. R. Welberry ◽  
A. Lee ◽  
K. Owen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Real Time ◽  
Two Dimensions ◽  
Computer Screen ◽  
Energy Parameters ◽  
Random Tiling ◽  
Tiling Patterns ◽  
Tile Pair

A program is described that demonstrates in two dimensions the concepts of quasiperiodic tiling and phason fluctuations. Tiling patterns having perfect fivefold or eightfold quasiperiodicity are displayed on the computer screen at any one of three chosen scales. These patterns are then progressively altered in real time by the application of phason flips to obtain disordered tiling patterns. Energy parameters may be specified to allow preference for different tile-pair combinations in the resulting distributions. In this way, with different combinations of the energies, distributions varying from pure random tiling to ones in which more ordered microdomains are to be seen may be obtained in real time via Monte Carlo simulation.

scholarly journals Monte Carlo simulation of abnormal grain growth in two dimensions

2001 ◽  
Vol 308 (1-2) ◽  
pp. 258-267 ◽  
Author(s):  
René Messina ◽  
Michèle Soucail ◽  
Ladislas Kubin
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Grain Growth ◽  
Two Dimensions ◽  
Abnormal Grain Growth

Q-COLOR PROBLEM IN D DIMENSIONS

1988 ◽  
Vol 02 (06) ◽  
pp. 1503-1511 ◽  
Author(s):  
C. Y. PAN ◽  
X. Y. CHEN
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Cell Growth ◽  
Recursion Formula ◽  
Two Dimensions ◽  
Three Dimensions ◽  
Four Dimensions ◽  
Color Problem ◽  
Hypercubic Lattice ◽  
Growth Method

Two methods are introduced to deal with the general q-color problem on a d-dimensional hypercubic lattice: one is the cell-growth method which gives an approximative solution of the problem in two and three dimensions, another is to combine the cell-growth method with the Monte Carlo simulation which leads to a recursion formula for the problem in d-dimensions. The results of both methods are in excellent agreement with Lieb's exact solution for the case of q = 3 in two dimensions and support Mattis' conjecture in the case of q > d, improve it in the case of 2 < q ≲ d. The validity of the recursion formula is supported by a Monte Carlo simulation up to four-dimensions.

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