# init_bounds_optim: Setting of Optimization Bounds and Initial Values In varycoef: Modeling Spatially Varying Coefficients

 init_bounds_optim R Documentation

## Setting of Optimization Bounds and Initial Values

### Description

Sets bounds and initial values for `optim` by extracting potentially given values from `SVC_mle_control` and checking them, or calculating them from given data. See Details.

### Usage

```init_bounds_optim(control, p, q, id_obj, med_dist, y_var, OLS_mu)
```

### Arguments

 `control` (`SVC_mle_control` output, i.e. `list`) `p` (`numeric(1)`) Number of fixed effects `q` (`numeric(1)`) Number of SVCs `id_obj` (`numeric(2*q+1+q)`) Index vector to identify the arguments of objective function. `med_dist` (`numeric(1)`) Median distance between observations `y_var` (`numeric(1)`) Variance of response `y` `OLS_mu` (`numeric(p)`) Coefficient estimates of ordinary least squares (OLS).

### Details

If values are not provided, then they are set in the following way. Let d be the median distance `med_dist`, let s^2_y be the variance of the response `y_var`, and let b_j be the OLS coefficients of the linear model. The computed values are given in the table below.

 Parameter Lower bound Initial Value Upper Bound Range d/1000 d/4 10 d Variance 0 s^2_y/(q+1) 10s^2_y Nugget 10^{-6} s^2_y/(q+1) 10s^2_y Mean j `-Inf` b_j `Inf`

### Value

A `list` with three entries: `lower`, `init`, and `upper`.

### Author(s)

Jakob Dambon

varycoef documentation built on Sept. 18, 2022, 1:07 a.m.