IRIS Toolbox Reference Manual

## neighbourhood

Evaluate the local behaviour of the objective function around the estimated parameter values

#### Syntax

    [D,FigH,AxH,ObjH,LikH,EstH,BH] = neighbourhood(M,PS,Neigh,...)

#### Input arguments

- `M` [ model | bkwmodel ] - Model or bkwmodel object.

- `PS` [ poster ] - Posterior simulator (poster) object returned by the `model/estimate` function.

- `Neigh` [ numeric ] - The neighbourhood in which the objective function will be evaluated defined as multiples of the parameter estimates.

#### Output arguments

- `D` [ struct ] - Struct describing the local behaviour of the objective function and the data likelihood (minus log likelihood) within the specified range around the optimum for each parameter.

The following output arguments are non-empty only if you choose `'plot='` true:

- `FigH` [ numeric ] - Handles to the figures created.

- `AxH` [ numeric ] - Handles to the axes objects created.

- `ObjH` [ numeric ] - Handles to the objective function curves plotted.

- `LikH` [ numeric ] - Handles to the data likelihood curves plotted.

- `EstH` [ numeric ] - Handles to the actual estimate marks plotted.

- `BH` [ numeric ] - Handles to the bounds plotted.

#### Options

- `'plot='` [ `true` | `false` ] - Call the `grfun.plotneigh` function from within `neighbourhood` to visualise the results.

- `'neighbourhood='` [ struct | empty ] - Struct specifying the neighbourhood points for some of the parameters; these points will be used instead of those based on `Neigh`.

#### Plotting options

See help on `grfun.plotneigh` for options available when you choose `'plot='` true.

#### Description

In the output database, `D`, each parameter is a 1-by-3 cell array. The first cell is a vector of parameter values at which the local behaviour was investigated. The second cell is a matrix with two column vectors: the values of the overall minimised objective function (as set up in the `estimate` function), and the values of the data likelihood component. The third cell is a vector of four numbers: the parameter estimate, the value of the objective function at optimum, the lower bound and the upper bound.

#### Example

IRIS Toolbox. Copyright © 2007—2013 Jaromir Benes.