The aim of this work is to propose and analyze the behavior of a test statistic to assess a parametric trend surface, that is, a regression model with spatially correlated errors. The asymptotic behavior under the null hypothesis, as well as the asymptotic power of the test under local alternatives will be analyzed. Finite sample performance of the test is addressed by simulation, introducing a bootstrap calibration procedure
Methods of assessing model fit for models of spatial flows frequently do not take account of spatial...
In this study, parametric bootstrap methods are used to test for spatial non-stationarity in the coe...
We develop a new method for assessing the adequacy of a smooth regression function, based on nonpara...
The aim of this work is to propose and analyze the behavior of a test statistic to assess a parametr...
Trátase dun resumo estendido da ponencia[Abstract] The aim of this work is to propose and analyze th...
We introduce and apply bootstrap method for testing spatial correlation in a linear regression model...
This paper presents a goodness-of-fit test for parametric regression models with scalar response and...
In this simulation study, parametric bootstrap methods are introduced to test for spatial non-statio...
This paper proposes omnibus and directional tests for testing the goodness-of-fit of a parametric re...
Kelejian (2008) introduces a J-type test for the situation in which a null linear regression model, ...
We develop non-nested tests in a general spatial, spatio-temporal or panel data context. The spatial...
Consider the nonparametric location-scale regression model Y = m(X) + sigma(X)epsilon, where the err...
This article proposes two new classes of nonparametric tests for the correct specification of linear...
This paper presents results from a Monte Carlo study concerning inference with spatially dependent d...
AbstractIn this study, parametric bootstrap methods are used to test for spatial non-stationarity in...
Methods of assessing model fit for models of spatial flows frequently do not take account of spatial...
In this study, parametric bootstrap methods are used to test for spatial non-stationarity in the coe...
We develop a new method for assessing the adequacy of a smooth regression function, based on nonpara...
The aim of this work is to propose and analyze the behavior of a test statistic to assess a parametr...
Trátase dun resumo estendido da ponencia[Abstract] The aim of this work is to propose and analyze th...
We introduce and apply bootstrap method for testing spatial correlation in a linear regression model...
This paper presents a goodness-of-fit test for parametric regression models with scalar response and...
In this simulation study, parametric bootstrap methods are introduced to test for spatial non-statio...
This paper proposes omnibus and directional tests for testing the goodness-of-fit of a parametric re...
Kelejian (2008) introduces a J-type test for the situation in which a null linear regression model, ...
We develop non-nested tests in a general spatial, spatio-temporal or panel data context. The spatial...
Consider the nonparametric location-scale regression model Y = m(X) + sigma(X)epsilon, where the err...
This article proposes two new classes of nonparametric tests for the correct specification of linear...
This paper presents results from a Monte Carlo study concerning inference with spatially dependent d...
AbstractIn this study, parametric bootstrap methods are used to test for spatial non-stationarity in...
Methods of assessing model fit for models of spatial flows frequently do not take account of spatial...
In this study, parametric bootstrap methods are used to test for spatial non-stationarity in the coe...
We develop a new method for assessing the adequacy of a smooth regression function, based on nonpara...