# make.proc: Process Distributions In CollocInfer: Collocation Inference for Dynamic Systems

## Description

Functions to define process distributions in the collocation inference package.

## Usage

 ```1 2 3 4 5``` ```make.Dproc() make.Cproc() make.SSEproc() ```

## Details

All functions require `more` to specify this distribution. This should be a list containing

• `fn` The distribution specified.

• `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.

For `Cproc` and `Dproc` this should specify the distribution; for `SSEproc` it should specify the right hand side of a differential equation.

## Value

A list of functions that the process distribution

 `make.Cproc` creates functions to evaluate the distribution of the derivative of the state vector given the current state for continuous-time systems. `make.Dproc` creates functions to evaluate the distribution of the next time point of the state vector given the current state for discrete-state systems. `make.SSEproc` treats the distribution of the derivative as an independent gaussian and cacluates weighted sums of squared errors between derivatives and the prediction from the current state.

`LS.setup`, `multinorm.setup`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```# FitzHugh-Nagumo Equations proc = make.SSEproc() proc\$more = make.fhn() # Henon Map proc = make.Dproc() proc\$more = make.Henon # SEIR with multivariate normal transitions proc = make.Cproc() proc\$more = make.multinorm() proc\$more\$more = c(make.SEIR(),make.var.SEIR()) ```