Transformation-based generalized spatial regression using the spmoran package: Case study examples

09/14/2021
by   Daisuke Murakami, et al.
0

This study presents application examples of generalized spatial regression modeling for count data and continuous non-Gaussian data using the spmoran package (version 0.2.2 onward). Section 2 introduces the model. The subsequent sections demonstrate applications of the model for disease mapping, spatial prediction and uncertainty modeling, and hedonic analysis. The R codes used in this vignette are available from https://github.com/dmuraka/spmoran. Another vignette focusing on Gaussian spatial regression modeling is also available from the same GitHub page.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 12

page 13

page 21

page 22

01/11/2021

Compositionally-warped additive mixed modeling for a wide variety of non-Gaussian spatial data

As with the advancement of geographical information systems, non-Gaussia...
12/02/2016

Voxelwise nonlinear regression toolbox for neuroimage analysis: Application to aging and neurodegenerative disease modeling

This paper describes a new neuroimaging analysis toolbox that allows for...
05/04/2022

DADApy: Distance-based Analysis of DAta-manifolds in Python

DADApy is a python software package for analysing and characterising hig...
03/12/2021

Fast, Scalable Approximations to Posterior Distributions in Extended Latent Gaussian Models

We define a novel class of additive models called Extended Latent Gaussi...
10/07/2020

Pkwrap: a PyTorch Package for LF-MMI Training of Acoustic Models

We present a simple wrapper that is useful to train acoustic models in P...
06/01/2019

Encouraging Equitable Bikeshare: Implications of Docked and Dockless Models for Spatial Equity

The last decade has seen a rapid rise in the number of bikeshare program...
04/23/2021

Eigenbackground Revisited: Can We Model the Background with Eigenvectors?

Using dominant eigenvectors for background modeling (usually known as Ei...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.