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Table 9 Results of regression model for fractional response variables Return rate Coef.
Lattice models with long-range interactions of power-law type are suggested as a new type of microscopic model for fractional non-local elasticity.
Motivated by [7, 14, 15], Yang and Hou [17] formulated a dual model for fractional minimax programming problem and proved duality theorems under generalized convex functions.
McDonald (2008) shows that the use of OLS, Tobit, and transformed logistic-normal model for fractional dependent variable data would yield inefficient results because the distribution of error terms is likely to be heteroskedastic.4 This is because, as the conditional variance of the error term approach zero, the conditional mean approaches either of the boundary points of the fractional data.
Bidirectional stepwise model selection was performed, yielding the final model for fractional shortening presented in Figure 1G.
The fractional logit model is a popular model for fractional response variables in econometrics and was proposed (independently) by Papke and Wooldridge [ 8] and by Cox [ 9].
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We construct the proposed model for fractional-order two-species facultative mutualism by improving system (1.1).
We formulate a new model for the fractional Boussinesq equation by using this new Taylor series expansion.
Soghra Nobakhtian [6] obtained optimality conditions and a mixed dual model for nonsmooth fractional multiobjective programming problems.
Erreygers and Kessels [4] introduced a rank-oriented decomposition that relies on a linear regression model for the fractional rank deviations.
This partitioning scheme, which is an extended version of the one initially proposed by Mond and Weir [7], was used by Yang [18] for formulating a generalized duality model for a multiobjective fractional programming problem.
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