R: Measuring model accuracy.

compare.estimate.and.truth {dmt} | R Documentation

## Measuring model accuracy.

### Description

Compare estimated parameters and the original parameters used to generate the toydata.

### Usage

    compare.estimate.and.truth(res, toy)

### Arguments

`res` | DependencyModel object.
`toy` | Toydata which was used to learn the model.

### Details

Given original data (including the original parameters) and model learned based on the data, compare the learned parameters to the original ones.

### Value

Vector with following elements

`wtw.x, wtw.y` | Correlation between the original and estimated values for W*t(W) for X and Y, respectively.
`phi.x, phi.y` | Correlation between the original and estimated values for phi for X and Y, respectively.

### Note

Additional tests added later.

### Author(s)

Leo Lahti leo.lahti@iki.fi

### References

See citation("dmt") for references.

### See Also

`generate.toydata`

### Examples

    # toy <- generate.toydata(N = N,
    #           zDim = zdim, xDim = xdim, yDim = ydim,
    #           marginal.covariances = marginalCovariances,
    #           priors = priors)
    # res <- fit.dependency.model(toy$X, toy$Y,
    #                      zDimension = zdim,
    #              marginalCovariances = marginalCovariances,
    #		      priors = priors,
    #                     matched = FALSE)
    # vec <- compare.estimate.and.truth(res, toy)
    #

[Package dmt version 0.8.20 Index]