Accessors {iprior}

Accessor functions for ipriorMod objects.

Description

Accessor functions for ipriorMod objects.

Usage

get_intercept(object)

get_y(object)

get_size(object, units = "kB", standard = "SI")

get_hyp(object)

get_lambda(object)

get_psi(object)

get_lengthscale(object)

get_hurst(object)

get_offset(object)

get_degree(object)

get_se(object)

get_kernels(object)

get_kern_matrix(object, theta = NULL, newdata)

get_prederror(object, error.type = c("RMSE", "MSE"))

get_estl(object)

get_method(object)

get_convergence(object)

get_niter(object)

get_time(object)

get_theta(object)

Arguments

object

An ipriorMod object.

units

Units for object size.

standard

Standard for object size.

theta

(Optional) Value of hyperparameters to evaluate the kernel matrix.

newdata

(Optional) If not supplied, then a square, symmetric kernel matrix is returned using the data as input points. Otherwise, the kernel matrix is evaluated with respect to this set of data as well. It must be a list of vectors/matrices with similar dimensions to the original data.

error.type

(Optional) Report the mean squared error of prediction ("MSE"), or the root mean squared error of prediction ("RMSE")

Functions

• get_intercept(): Obtain the intercept.

• get_y(): Obtain the response variables.

• get_size(): Obtain the object size of the I-prior model.

• get_hyp(): Obtain the hyerparameters of the model (both estimated and fixed ones).

• get_lambda(): Obtain the scale parameters used.

• get_psi(): Obtain the error precision.

• get_lengthscale(): Obtain the lengthscale for the SE kernels used.

• get_hurst(): Obtain the Hurst coefficient of the fBm kernels used.

• get_offset(): Obtain the offset parameters for the polynomial kernels used.

• get_degree(): Obtain the degree of the polynomial kernels used.

• get_se(): Obtain the standard errors of the estimated hyperparameters.

• get_kernels(): Obtain the kernels used.

• get_kern_matrix(): Obtain the kernel matrix of the I-prior model.

• get_prederror(): Obtain the training mean squared error.

• get_estl(): Obtain information on which hyperparameters were estimated and which were fixed.

• get_method(): Obtain the estimation method used.

• get_convergence(): Obtain the convergence information.

• get_niter(): Obtain the number of iterations performed.

• get_time(): Obtain the time taken to complete the estimation procedure.

• get_theta(): Extract the theta value at convergence. Note that this is on an unrestricted scale (see the vignette for details).