6 citations · 12 across the 6 of their papers we have counts for
4 papers · 1 filter
A Generalized Spatial Correlated Mean Component Model: Theory and Application to U.S. County Voting Data
N. A. Cruz, J. D. Toloza-Delgado, O. O. Melo
This paper introduces the generalized spatial correlated inverse mean component (GSCIMC), a flexible and computationally efficient framework for modeling spatial dependence in non-…
Analysis of longitudinal data with destructive sampling using linear mixed models
C. A. Avellaneda, O. O. Melo, N. A. Cruz
This paper proposes an analysis methodology for the case where there is longitudinal data with destructive sampling of observational units, which come from experimental units that…
Spatial error models with heteroskedastic normal perturbations and joint modeling of mean and variance
J. D. Toloza, O. O. Melo, N. A. Cruz
This work presents the spatial error model with heteroskedasticity, which allows the joint modeling of the parameters associated with both the mean and the variance, within a tradi…
Joint spatial modeling of mean and non-homogeneous variance combining semiparametric SAR and GAMLSS models for hedonic prices
J. D. Toloza-Delgado, O. O. Melo, N. A. Cruz
In the context of spatial econometrics, it is very useful to have methodologies that allow modeling the spatial dependence of the observed variables and obtaining more precise pred…