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varycoef (version 0.3.2)

Modeling Spatially Varying Coefficients

Description

Implements a maximum likelihood estimation (MLE) method for estimation and prediction of Gaussian process-based spatially varying coefficient (SVC) models (Dambon et al. (2021a) ). Covariance tapering (Furrer et al. (2006) ) can be applied such that the method scales to large data. Further, it implements a joint variable selection of the fixed and random effects (Dambon et al. (2021b) ). The package and its capabilities are described in (Dambon et al. (2021c) ).

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Install

install.packages('varycoef')

Monthly Downloads

577

Version

0.3.2

License

GPL-2

Issues

3

Pull Requests

1

Stars

13

Forks

3

Maintainer

Jakob Dambon

Last Published

April 27th, 2022

Functions in varycoef (0.3.2)

Sigma_y

Covariance Matrix of GP-based SVC Model
SVC_selection

SVC Model Selection
GLS_chol

GLS Estimate using Cholesky Factor
coef.SVC_mle

Extact Mean Effects
SVC_selection_control

SVC Selection Parameters
check_cov_lower

Check Lower Bound of Covariance Parameters
SVC_mle

MLE of SVC model
IC.SVC_mle

Conditional Akaike's and Bayesian Information Criteria
cov_par

Extact Covariance Parameters Function to extract the covariance parameters from an SVC_mle or SVC_selectionobject.
own_dist

Computes (Cross-) Distances
fitted.SVC_mle

Extact Model Fitted Values
predict.SVC_mle

Prediction of SVCs (and response variable)
prep_par_output

Preparation of Parameter Output
SVC_mle_control

Set Parameters for SVC_mle
init_bounds_optim

Setting of Optimization Bounds and Initial Values
plot.SVC_mle

Plotting Residuals of SVC_mle model
logLik.SVC_mle

Extact the Likelihood
fullSVC_reggrid

Sample Function for GP-based SVC Models on Regular Grid
house

Lucas County House Price Data
nlocs

Extract Number of Unique Locations Function to extract the number of unique locations in the data set used in an MLE of the SVC_mle object.
fullSVC_line

Sample Function for GP-based SVC Model on Real Line
varycoef

varycoef: Modeling Spatially Varying Coefficients
summary.SVC_mle

Summary Method for SVC_mle
residuals.SVC_mle

Extact Model Residuals
sample_fullSVC

Sample Function for GP-based SVC Model for Given Locations
print.SVC_mle

Print Method for SVC_mle
print.summary.SVC_mle

Printing Method for summary.SVC_mle
nobs.SVC_mle

Extact Number of Observations