sp_bgsmtr_path: A Bayesian Spatial Model for Imaging Genetics

Description Usage Arguments Value Author(s) References Examples

View source: R/all_functions.R

Description

A plotting function can be used to demonstrate the regularization paths for estimating parameters of each ROI when the spatial model is fitted with multiple values of tuning parameter lambda-squared.

Usage

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sp_bgsmtr_path(lambda_v, W_est_list)

Arguments

lambda_v

A vector containing all the different tuning parameter lambda-squared values for model fitting.

W_est_list

A list containing all the estimated coefficients matrices W for each corresponding lambda squared value used in lambda_v for model fitting. Each element of this list is a d-by-c matrix.

Value

Regularization plots files in PDF format for each ROI.

Author(s)

Yin Song, yinsong@uvic.ca

Shufei Ge, shufeig@sfu.ca

Farouk S. Nathoo, nathoo@uvic.ca

Liangliang Wang, lwa68@sfu.ca

Jiguo Cao, jiguo_cao@sfu.ca

References

Song, Y., Ge, S., Cao, J., Wang, L., Nathoo, F.S., A Bayesian Spatial Model for Imaging Genetics. arXiv:1901.00068.

Examples

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data(sp_bgsmtr_example_data$path_data)


## Not run: 

# Creating the regulazaition path plots  as follow:
sp_bgsmtr_path(lambda_v = sp_bgsmtr_example_data$path_data$lambda_v,
 W_est_list = sp_bgsmtr_example_data$path_data$W_est_list )


## End(Not run)

bgsmtr documentation built on Dec. 16, 2019, 1:35 a.m.