Creates an INLA object for a stationary Matern model with general smoothness parameter.

## Usage

```
rspde.matern(
mesh,
nu_upper_bound = 4,
rspde_order = 2,
nu = NULL,
debug = FALSE,
prior.kappa = NULL,
prior.nu = NULL,
prior.tau = NULL,
prior.range = NULL,
prior.std.dev = NULL,
start.lkappa = NULL,
start.nu = NULL,
start.ltau = NULL,
start.lrange = NULL,
start.lstd.dev = NULL,
parameterization = c("matern", "spde"),
prior.nu.dist = c("lognormal", "beta"),
nu.prec.inc = 1,
type.rational.approx = c("chebfun", "brasil", "chebfunLB"),
shared_lib = "INLA"
)
```

## Arguments

- mesh
The mesh to build the model. It can be an

`inla.mesh`

or an`inla.mesh.1d`

object. Otherwise, should be a list containing elements d, the dimension, C, the mass matrix, and G, the stiffness matrix.- nu_upper_bound
Upper bound for the smoothness parameter.

- rspde_order
The order of the covariance-based rational SPDE approach.

- nu
If nu is set to a parameter, nu will be kept fixed and will not be estimated. If nu is

`NULL`

, it will be estimated.- debug
INLA debug argument

- prior.kappa
a

`list`

containing the elements`meanlog`

and`sdlog`

, that is, the mean and standard deviation on the log scale.- prior.nu
a list containing the elements

`mean`

and`prec`

for beta distribution, or`loglocation`

and`logscale`

for a truncated lognormal distribution.`loglocation`

stands for the location parameter of the truncated lognormal distribution in the log scale.`prec`

stands for the precision of a beta distribution.`logscale`

stands for the scale of the truncated lognormal distribution on the log scale. Check details below.- prior.tau
a list containing the elements

`meanlog`

and`sdlog`

, that is, the mean and standard deviation on the log scale.- prior.range
a

`list`

containing the elements`meanlog`

and`sdlog`

, that is, the mean and standard deviation on the log scale. Will not be used if prior.kappa is non-null.- prior.std.dev
a

`list`

containing the elements`meanlog`

and`sdlog`

, that is, the mean and standard deviation on the log scale. Will not be used if prior.tau is non-null.- start.lkappa
Starting value for log of kappa.

- start.nu
Starting value for nu.

- start.ltau
Starting value for log of tau.

- start.lrange
Starting value for log of range. Will not be used if start.lkappa is non-null.

- start.lstd.dev
Starting value for log of std. deviation. Will not be used if start.ltau is non-null.

- parameterization
Which parameterization to use?

`matern`

uses range, std. deviation and nu (smoothness).`spde`

uses kappa, tau and nu (smoothness). The default is`matern`

.- prior.nu.dist
The distribution of the smoothness parameter. The current options are "beta" or "lognormal". The default is "beta".

- nu.prec.inc
Amount to increase the precision in the beta prior distribution. Check details below.

- type.rational.approx
Which type of rational approximation should be used? The current types are "chebfun", "brasil" or "chebfunLB".

- shared_lib
Which shared lib to use for the cgeneric implementation? If "INLA", it will use the shared lib from INLA's installation. If 'rSPDE', then it will use the local installation (does not work if your installation is from CRAN). Otherwise, you can directly supply the path of the .so (or .dll) file.