Correlation and variable importance in random forests

This paper is about variable selection with the random forests algorithm in presence of correlated predictors. In high-dimensional regression or classification frameworks, variable selection is a difficult task, that becomes even more challenging in the presence of highly correlated predictors. Firstly we provide a theoretical study of the permutation importance measure for an additive regression model. This allows us to describe how the correlation between predictors impacts the permutation importance. Our results motivate the use of the recursive feature elimination (RFE) algorithm for variable selection in this context. This algorithm recursively eliminates the variables using permutation importance measure as a ranking criterion. Next various simulation experiments illustrate the efficiency of the RFE algorithm for selecting a small number of variables together with a good prediction error. Finally, this selection algorithm is tested on the Landsat Satellite data from the UCI Machine Learning Repository.     

Asymptotic behaviour of binned kernel density estimators for locally non-stationary random fields

We investigate the asymptotic behaviour of binned kernel density estimators for dependent and locally non-stationary random fields converging to stationary random fields. We focus on the study of the bias and the asymptotic normality of the estimators. A simulation experiment conducted shows that both the kernel density estimator and the binned kernel density estimator have the same behavior and both estimate accurately the true density when the number of fields increases. We apply our results to the 2002 incidence rates of tuberculosis in the departments of France.     

FACILITATING INTIMACY: INTERVENTIONS AND EFFECTS

The Present study investigated by effects of two sets of marital interventions taken from Emotionally Focused Therapy (EFT) and Cognitive Marital Therapy (CMT) on level of marital intimacy, dyadic trust, and dyadic adjustment. It was hypothesized that both EFT and CMT would have a positive effect on levels of intimacy, trust, and adjustment as compared to a wait-list control group and that there would be a differential effect in favor of EFT as compared to CMT. Thirty-six couples free of marital distress and seeking to enhance theor intimate relationship were randomaly assigned to EFT, CMT, or a wai-list control group. Therapists' interventions were monitored and found to be faithfully implemented. Groups were equivalent on demographic variables and the quality of the therapeutic alliance. Both EFT and CMT group posttest means were found to be significantly higher than controls on the self-report measures of intimacy, Observational measures of intimacy revealed differential effects in favor of EFT as comopared to CMT at posttest. At a 10-week follow-up, EFT group means were significantly higher than CMT on self-reported intimacy and adjustment.     

Immigration and internal mobility in Canada

We analyse the impact of temporary foreign workers (TFWs) and permanent immigrants on interprovincial mobility in Canada. Empirical results are analysed through the lens of a theoretical model that incorporates a job-matching framework in a migration model à la Harris and Todaro. The effect of the inflow of TFWs in interprovincial mobility is negative, substantial and significant. This is not the case for the inflow of permanent immigrants selected through the Canadian point system. The robustness of these empirical results to issues of endogeneity is assessed through a classical instrumentation approach as well as through a diff-in-diff analysis taking advantage of a pilot project facilitating the admission of TFWs in two Western provinces over the 2007–2010 period. Our paper suggests that, in general, the impact of immigration on labour market conditions depends critically on the way immigration policy is set.     

Bayesian Inference in Dynamic Disequilibrium Models: An Application to the Polish Credit Market

We propose a Bayesian approach for inference in a dynamic disequilibrium model. To circumvent the difficulties raised by the Maddala and Nelson (1974) specification in the dynamic case, we analyze a dynamic extended version of the disequilibrium model of Ginsburgh et al. (1980). We develop a Gibbs sampler based on the simulation of the missing observations. The feasibility of the approach is illustrated by an empirical analysis of the Polish credit market, for which we conduct a specification search using the posterior deviance criterion of Spiegelhalter et al. (2002).