# Create INLA mesh for spatial analysis

`compute_mesh.Rd`

`compute_mesh`

create objects required for INLA analysis of an object of class `"CRTsp"`

.

## Usage

```
compute_mesh(
trial = trial,
offset = -0.1,
max.edge = 0.25,
inla.alpha = 2,
maskbuffer = 0.5,
pixel = 0.5
)
```

## Arguments

- trial
an object of class

`"CRTsp"`

or a data frame containing locations in (x,y) coordinates, cluster assignments (factor`cluster`

), and arm assignments (factor`arm`

) and outcome.- offset
see

`inla.mesh.2d`

documentation- max.edge
see

`inla.mesh.2d`

documentation- inla.alpha
parameter related to the smoothness (see

`inla`

documentation)- maskbuffer
numeric: width of buffer around points (km)

- pixel
numeric: size of pixel (km)

## Value

list

`prediction`

Data frame containing the prediction points and covariate values`A`

projection matrix from the observations to the mesh nodes.`Ap`

projection matrix from the prediction points to the mesh nodes.`indexs`

index set for the SPDE model`spde`

SPDE model`pixel`

pixel size (km)

## Details

`compute_mesh`

carries out the computationally intensive steps required for setting-up an
INLA analysis of an object of class `"CRTsp"`

, creating the prediction mesh and the projection matrices.
The mesh can be reused for different models fitted to the same
geography. The computational resources required depend largely on the resolution of the prediction mesh.
The prediction mesh is thinned to include only pixels centred at a distance less than
`maskbuffer`

from the nearest point.

A warning may be generated if the `Matrix`

library is not loaded.