coef_marginal

This function evaluates the marginal effects from x (dy/dx) based on the estimation result of <code>resf</code>. This funtion is for non-Gaussian models transforming y using <code>nongauss_y</code>.

A collection of functions for estimating spatial and spatio-temporal regression models. Moran eigenvectors are used as spatial basis functions to efficiently approximate spatially dependent Gaussian processes (i.e., random effects eigenvector spatial filtering; see Murakami and Griffith 2015 <doi: 10.1007/s10109-015-0213-7>). The implemented models include linear regression with residual spatial dependence, spatially/spatio-temporally varying coefficient models (Murakami et al., 2017, 2024; <doi:10.1016/j.spasta.2016.12.001>,<doi:10.48550/arXiv.2410.07229>), spatially filtered unconditional quantile regression (Murakami and Seya, 2019 <doi:10.1002/env.2556>), Gaussian and non-Gaussian spatial mixed models through compositionally-warping (Murakami et al. 2021, <doi:10.1016/j.spasta.2021.100520>).

Daisuke Murakami

spmoran

Fast Spatial and Spatio-Temporal Regression using Moran
Eigenvectors

coef_marginal function

<dl><dt>mod</dt>
<dd>Output from <code>resf</code></dd></dl>

Arguments

Marginal effects evaluation — coef_marginal

<dl>

<dt>mod</dt>
<dd>Output from <code>resf</code></dd>

</dl>

coef_marginal: Marginal effects evaluation

Description

Usage

Value

Arguments

See Also