make.lik {CollocInfer} | R Documentation |

## Observation Process Distribution Function

### Description

Returns a list of functions that calculate the observation process distribution and its derivatives; designed to be used with the collocation inference functions.

### Usage

```
make.SSElik()
make.multinorm()
```

### Details

These functions require `more`

to be a list with elements:

`fn`

The transform function of the states to observations, or to their derivatives.`dfdx`

The derivative of`fn`

with respect to states.`dfdp`

The derivative of`fn`

with respect to parameters.`d2fdx2`

The second derivative of`fn`

with respect to states.`d2fdxdp`

The cross derivative of`fn`

with respect to states and parameters.

`make.Multinorm`

further requires:

`var.fn`

The variance given in terms of states and parameters.`var.dfdx`

The derivative of`var.fn`

with respect to states.`var.dfdp`

The derivative of`var.fn`

with respect to parameters.`var.d2fdx2`

The second derivative of`var.fn`

with respect to states.`var.d2fdxdp`

The cross derivative of`var.fn`

with respect to states and parameters.

`make.SSElik`

further requres `weights`

giving weights to each observation.

### Value

A list of functions that calculate the log observation distribution and its derivatives.

`make.SSElik` |
calculates weighted squared error between predictions
(given by |

`make.Multinorm` |
calculates a multivariate normal distribution. |

### See Also

### Examples

```
# Straightforward sum of squares:
lik = make.SSElik()
lik$more = make.id()
# Multivariate normal about an exponentiated state with constant variance
lik = make.multinorm()
lik$more = c(make.exp(),make.cvar())
```

*CollocInfer*version 1.0.4 Index]