Estimation and computational evaluation of the coefficient of intraspecific competition in edges in the context of linear models

In experimental trials, it is usually of interest to give special regard to the response of experimental units at the edges, since it is well known that the performance of these can be greater than that of the rest of the units due to having less competition from neighboring units. When treatments are available, it is possible that the differences in the mean crop response are attributable to the edge effect. Therefore, it is important to consider the edge or not in the modeling process. In this case, using the Kempton-Besag model and the reparameterization of the model, the intraspecific competition coefficient was estimated through least quadratic estimation that in this case was associated with the edge effect. Its distributional pattern was studied using Monte Carlo simulation. Simulated variance analyses were carried out to see the distributional effect of the F-statistic in the presence of the edge effect as a form of spatial dependence that was evaluated with the Moran index. The coefficient associated with the edge effect showed a clear normal distribution in all the considered edge scenarios. The sign of the coefficient and the confidence intervals generated made it possible to discriminate the presence/absence of edge effect. In addition, a method was proposed to allow a user to mitigate the fuzziness that may result from the point estimate of the coefficient. This procedure can be used in other neighborhood patterns and other design models of importance in agricultural research.Keywords: border effect, competition coefficient, reparameterization, Monte Carlo Simulation