# sde.valid: SDE data and parameter validators. In msde: Bayesian Inference for Multivariate Stochastic Differential Equations

## Description

Checks whether input SDE data and parameters are valid.

## Usage

 ```1 2 3``` ```sde.valid.data(model, x, theta) sde.valid.params(model, theta) ```

## Arguments

 `model` An `sde.model` object. `x` A length-`ndims` vector or `ndims`-column matrix of SDE data. `theta` A length-`nparams` vector or `nparams`-column of SDE parameter values.

## Value

A logical scalar or vector indicating whether the given data/parameter pair is valid.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```# Heston's model # valid data is: Z > 0 # valid parameters are: gamma, sigma > 0, |rho| < 1, beta > .5 * sigma^2 hmod <- sde.examples("hest") # load model theta <- c(alpha = 0.1, gamma = 1, beta = 0.8, sigma = 0.6, rho = -0.8) # valid data x0 <- c(X = log(1000), Z = 0.1) sde.valid.data(model = hmod, x = x0, theta = theta) # invalid data x0 <- c(X = log(1000), Z = -0.1) sde.valid.data(model = hmod, x = x0, theta = theta) # valid parameters theta <- c(alpha = 0.1, gamma = 1, beta = 0.8, sigma = 0.6, rho = -0.8) sde.valid.params(model = hmod, theta = theta) # invalid parameters theta <- c(alpha = 0.1, gamma = -4, beta = 0.8, sigma = 0.6, rho = -0.8) sde.valid.params(model = hmod, theta = theta) ```

msde documentation built on May 2, 2019, 2:05 a.m.