make.lik {CollocInfer}

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 fn in more) and observations

make.Multinorm

calculates a multivariate normal distribution.

See Also

LS.setup, multinorm.setup

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())