Description Usage Arguments Value See Also Examples
Load the kernel matrices for Iprior models
1 2 3 4 5 6 7 8 9 10 11 12  kernL(y, ..., kernel = "linear", interactions = NULL,
est.lambda = TRUE, est.hurst = FALSE, est.lengthscale = FALSE,
est.offset = FALSE, est.psi = TRUE, fixed.hyp = NULL, lambda = 1,
psi = 1, nystrom = FALSE, nys.seed = NULL, model = list(),
train.samp, test.samp)
## S3 method for class 'formula'
kernL(formula, data, kernel = "linear",
one.lam = FALSE, est.lambda = TRUE, est.hurst = FALSE,
est.lengthscale = FALSE, est.offset = FALSE, est.psi = TRUE,
fixed.hyp = NULL, lambda = 1, psi = 1, nystrom = FALSE,
nys.seed = NULL, model = list(), train.samp, test.samp, ...)

y 
Vector of response variables 
... 
Only used when fitting using nonformula, enter the variables (vectors or matrices) separated by commas. 
kernel 
Character vector indicating the type of kernel for the variables. Available choices are:
The 
interactions 
Character vector to specify the interaction terms. When
using formulas, this is specified automatically, so is not required. Syntax
is 
est.lambda 
Logical. Estimate the scale parameters? Defaults to

est.hurst 
Logical. Estimate the Hurst coefficients for fBm kernels?
Defaults to 
est.lengthscale 
Logical. Estimate the lengthscales for SE kernels?
Defaults to 
est.offset 
Logical. Estimate the offsets for polynomial kernels?
Defaults to 
est.psi 
Logical. Estimate the error precision? Defaults to

fixed.hyp 
Logical. If 
lambda 
Initial/Default scale parameters. Relevant especially if

psi 
Initial/Default value for error precision. Relevant especially if

nystrom 
Either logical or an integer indicating the number of Nystrom
samples to take. Defaults to 
nys.seed 
The random seed for the Nystrom sampling. Defaults to

model 
DEPRECATED. 
train.samp 
(Optional) A vector indicating which of the data points should be used for training, and the remaining used for testing. 
test.samp 
(Optional) Similar to 
formula 
The formula to fit when using formula interface. 
data 
Data frame containing variables when using formula interface. 
one.lam 
Logical. When using formula input, this is a convenient way of
letting the function know to treat all variables as a single variable (i.e.
shared scale parameter). Defaults to 
An ipriorKernel
object which contains the relevant material to
be passed to the iprior
function for model fitting.
iprior
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  str(ToothGrowth)
(mod < kernL(y = ToothGrowth$len,
supp = ToothGrowth$supp,
dose = ToothGrowth$dose,
interactions = "1:2"))
kernL(len ~ supp * dose, data = ToothGrowth) # equivalent formula call
# Choosing different kernels
str(stackloss)
kernL(stack.loss ~ ., stackloss, kernel = "fbm") # all fBm kernels
kernL(stack.loss ~ ., stackloss, kernel = "FBm") # cApS dOn't MatTeR
kernL(stack.loss ~ ., stackloss,
kernel = c("linear", "se", "poly3")) # different kernels
# Sometimes the print output is too long, can use str() options here
print(mod, strict.width = "cut", width = 30)

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