6 citations · 12 across the 6 of their papers we have counts for
6 papers · 1 filter
SAR models with specific spatial coefficients and heteroskedastic innovations
N. A. Cruz, D. A. Romero, O. O. Melo
This paper presents an innovative extension of spatial autoregressive (SAR) models, introducing spatial coefficients specific to each spatial region that evolve over time. The prop…
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…
A correlation structure for the analysis of Gaussian and non-Gaussian responses in crossover experimental designs with repeated measures
N. A. Cruz, O. O. Melo, C. A. Martinez
In this study, we propose a family of correlation structures for crossover designs with repeated measures for both, Gaussian and non-Gaussian responses using generalized estimating…