aux_mat

single_dists

mult_dists

pred_cdist

get_grid_list

dist_from_grids

mult_dist_from_grids

Pairwise distances for a list of matrices (Internal use)
Cross-distances for two lists of matrices (Eigen version)
Prediction cross-distances (Eigen version)

internal

Provides functions to estimate, predict and interpolate areal
data. For estimation and prediction we assume areal data is an average
of an underlying continuous spatial process as in Moraga et
al. (2017) <doi:10.1016/j.spasta.2017.04.006>, Johnson et al. (2020)
<doi:10.1186/s12942-020-00200-w>, and Wilson and Wakefield (2020)
<doi:10.1093/biostatistics/kxy041>. The interpolation methodology is
(mostly) based on Goodchild and Lam (1980, ISSN:01652273).

Lucas da Cunha Godoy

smile

Spatial Misalignment: Interpolation, Linkage, and Estimation

aux_mat function

<dl><dt>mat_list</dt>
<dd>internal use</dd>
<dt>mat_list1</dt>
<dd>internal use</dd>
<dt>mat_list2</dt>
<dd>internal use</dd>
<dt>return_single</dt>
<dd>internal use</dd>
<dt>pred_mat</dt>
<dd>internal use</dd>
<dt>x_to_list</dt>
<dd>internal use</dd>
<dt>by</dt>
<dd>internal use</dd>
<dt>y_grid</dt>
<dd>internal use</dd>
<dt>x_grid</dt>
<dd>internal use</dd></dl>

Arguments

Pairwise distances for a list of matrices (Internal use) — aux_mat

<dl>

<dt>mat_list</dt>
<dd>internal use</dd>


<dt>mat_list1</dt>
<dd>internal use</dd>


<dt>mat_list2</dt>
<dd>internal use</dd>


<dt>return_single</dt>
<dd>internal use</dd>


<dt>pred_mat</dt>
<dd>internal use</dd>


<dt>x_to_list</dt>
<dd>internal use</dd>


<dt>by</dt>
<dd>internal use</dd>


<dt>y_grid</dt>
<dd>internal use</dd>


<dt>x_grid</dt>
<dd>internal use</dd>

</dl>

aux_mat: Pairwise distances for a list of matrices (Internal use)

Description

Usage

Arguments