References of "Akossou, A. Y. J"
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See detailImpact of Data Structure on the Estimators R-Square and adjusted R-Square in Linear Regression
Akossou, A. Y. J.; Palm, Rodolphe ULg

in International Journal of Mathematics and Computation (2013), 20(3), 84-93

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See detailValidity Limit of the Linear Regression Models for the Prediction
Akossou, A. Y. J.; Palm, Rodolphe ULg

in International Journal of Applied Mathematics & Statistics (2010), 16(M10), 38-48

Monte Carlo simulation methods was used to study the effects of the data structure on the quality of the predictions in linear multiple regression. Five hundred forty (540) data files were generated of ... [more ▼]

Monte Carlo simulation methods was used to study the effects of the data structure on the quality of the predictions in linear multiple regression. Five hundred forty (540) data files were generated of which the number of variables, R-square, the collinearity between the explanatory variables and the index of coefficient, that measures the importance of the explanatory variables in the model, were controlled. Predictions were influenced by the theoretical value of R-square, the method used to establish the model and, to a lesser extent, the collinearity between the explanatory variables. The determination of the minimal sample size which leads to predicted values better than those obtained by the mean of the dependant variable indicated that this size depends on the number of the explanatory variables, the theretical value of the R-square and the method used to establish the model. The minimal sample size increases with the models without variables selection and gradually decreases with the intensity of the selection. [less ▲]

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See detailSur l'erreur résiduelle obtenue en régression linéaire multiple.
Akossou, A. Y. J.; Palm, Rodolphe ULg; Fonton, N. H. et al

Scientific conference (2007)

The residual error is one of the most used criteria for the choice of regression model. The large majority of the criteria for model selection are also functions of the usual variance estimate for a ... [more ▼]

The residual error is one of the most used criteria for the choice of regression model. The large majority of the criteria for model selection are also functions of the usual variance estimate for a regression model, as Akaike criterion information [Akaike, 1973] and Mallows’ criterion [Mallows, 1964]. The effectiveness of these criteria to approach the theoretical model is related to the good estimate of the theoretical residual error of the model. This efficiency is often limited by the sample size used for the estimates. The choice of a invalid model can have bad consequences on the objective of the research in particular on the forecasts, interpretations and the conclusions. We studied by Monte Carlo simulation the effects of the data structure on the quality of the residual error obtained in multiple linear regression. The results showed that the estimator is a good estimator when the model is established without selection of variables, but becomes biased when the model results from a selection of variables. Colinearity between the explanatory variables and the index which measure the importance of the variables in the true model do not have an influence on the quality of the estimator. [less ▲]

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See detailConséquences de la sélection de variables sur l'interprétation des résultats en régression linéaire multiple
Akossou, A. Y. J.; Palm, Rodolphe ULg

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE] (2005), 9(1), 11-18

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See detailIntroduction à la programmation avec Matlab sous windows
Akossou, A. Y. J.; Fonton, N. H.; Claustriaux, Jean-Jacques ULg

in Notes de Biométrie et d'Informatique (2001), 2

This note aims to introduce Matlab software. Through this presentation we show a few advantages of the software. This presentation is then illustrated by a few examples of program with the software.

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See detailModèle de productivité et tarif de cubage des peuplements de teck (tectona grandis L. F.) au Sud-Bénin
Fonton, N. H.; Palm, Rodolphe ULg; Akossou, A. Y. J. et al

in Annales des Sciences Agronomiques du Bénin (2001), 2(2), 209-224

This study aims to build site index model and stem volume function of pure, even aged and relatively homogeneous teak stands in south Benin. The characteristics of the stands were obtained from the ... [more ▼]

This study aims to build site index model and stem volume function of pure, even aged and relatively homogeneous teak stands in south Benin. The characteristics of the stands were obtained from the inventory of 104 temporary plots sampled from stands with different ages and fertility. The stem analysis of 19 dominant trees wer used to establish, by serial regression, a model giving the evolution of top height according to the age. The site index curves were built in order to determine site index of the stands. The estimated volume function obtained shows that age, site index and basal area are the main stand parameters of stem volume funtion. [less ▲]

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