constructModel: Constructing GP model with the specified kernels
In GPrank: Gaussian Process Ranking of Multiple Time Series

Description Usage Arguments Value Author(s) Examples

Function for constructing the GP model with the specified kernels (and parameters).

1	constructModel(x, y, v, kernelTypes, params = NULL)

`x`	One-column matrix which contains the input values, i.e., time points for GP models. The values given in this vector are used in GP model, so if any transformation is needed, remember to transform them before constructing the model.
`y`	One-column matrix which contains the observed values at the corresponding time points given in the `x` vector.
`v`	One-column matrix which contains the fixed variances at the corresponding time points given in the `x` vector, with the corresponding observations given in the `y` vector.
`kernelTypes`	Character vector which contains the types of the kernels which will be used in the GP models. Kernel types: `'rbf'`, `'white'`, `'bias'`, `'fixedvariance'`. Note that the lower bound for the length scale parameter of rbf kernel is set to the minimum distance between consecutive time points in order to mitigate potential overfitting problems.
`params`	Values of the kernel parameters in their transformed form. If not specified, default values are assigned.

Return GP model constucted with the specified kernel settings.

Hande Topa, hande.topa@helsinki.fi

x=as.matrix(seq(1,10))
y=as.matrix(sin(x))
v=as.matrix(runif(10,0,0.5))
kernelTypes=c("rbf","white","fixedvariance")
model=constructModel(x,y,v,kernelTypes)