rsaeGWR: rsaeGWR: A package for robust small area estimation under...
In baldermann/rsaeGWR: Robust small area estimation under spatial non-stationarity
Description
The fit functions
The predrict function
Description
The package provides two categories of important functions:
fit and predict.
The fit functions
The fit functions gwlmm and rgwlmm fit a geographically weighted
linear mixed model (GWLMM) to data. The GWLMM is a nested error regression model that takes
into account spatial non-stationarity. The function gwlmm assumes normality
for the error term components. This assumption can be violated in the presence
of outliers. The function rgwlmm fits an outlier robust version of the GWLMM to the data.
The predrict function
The predict functions predict.gwlmm and predict.rgwlmm estimate
small area means based on the model fits from the fit funtions when population data is provided.
As predcision measures MSE estiamtes are provided.
The predict functions can handle aggregated population information with centroid coordinates and
unit-level population data with coordinates for each unit.
If no data is provided these functions provide the in-sample predictions
(random effects, residuals, etc.) based on the model fits.
baldermann/rsaeGWR documentation built on May 6, 2019, 2:19 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description The fit functions The predrict function
Description
The package provides two categories of important functions: fit and predict.
The fit functions
The fit functions gwlmm and rgwlmm fit a geographically weighted
linear mixed model (GWLMM) to data. The GWLMM is a nested error regression model that takes
into account spatial non-stationarity. The function gwlmm assumes normality
for the error term components. This assumption can be violated in the presence
of outliers. The function rgwlmm fits an outlier robust version of the GWLMM to the data.
The predrict function
The predict functions predict.gwlmm and predict.rgwlmm estimate
small area means based on the model fits from the fit funtions when population data is provided.
As predcision measures MSE estiamtes are provided.
The predict functions can handle aggregated population information with centroid coordinates and
unit-level population data with coordinates for each unit.
If no data is provided these functions provide the in-sample predictions
(random effects, residuals, etc.) based on the model fits.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.