Fix documentation

.gitignore

@@ -17,3 +17,4 @@ vignettes/cache
 *.texpadtmp
 /doc/
 /Meta/
+.DS_Store

DESCRIPTION

@@ -35,4 +35,4 @@ LazyData: yes
 VignetteBuilder: 
   knitr,
   R.rsp
-RoxygenNote: 7.3.1
+RoxygenNote: 7.2.3

NAMESPACE

@@ -24,45 +24,8 @@ S3method(print,time)
 S3method(sigma,ipriorMod)
 S3method(summary,ipriorMod)
 S3method(update,ipriorMod)
-export(.A_times_a)
-export(.calc_Hlam)
-export(.checkLevels)
-export(.collapse_param)
-export(.convert_se)
-export(.correct_pearson_kernel)
-export(.deal_with_one.lam)
-export(.eigen_Hlam)
-export(.eigen_Hlam_nys)
-export(.em_loop_logical)
-export(.expand_Hl_and_lambda)
-export(.expand_theta)
-export(.fix_call_default)
-export(.fix_call_formula)
-export(.formula_to_xy)
-export(.get_Hl)
-export(.get_Hlam)
-export(.get_Htildelam)
-export(.get_Xl.nys)
-export(.get_hyperparam)
-export(.get_kernels_from_Hl)
-export(.get_polydegree)
-export(.get_y_and_levels)
-export(.iprior_method_checker)
-export(.is.categorical)
-export(.is.ipriorKernel_cv)
 export(.kernel_summary_translator)
-export(.kernel_to_param)
-export(.kernel_translator)
 export(.kernels_for_summary)
-export(.param_to_kernel)
-export(.param_to_theta)
-export(.param_translator)
-export(.reduce_theta)
-export(.terms_to_xy)
-export(.theta_to_collapsed_param)
-export(.theta_to_kernel)
-export(.theta_to_param)
-export(.update_control)
 export(as.time)
 export(check_theta)
 export(dec_plac)

R/Kernel_functions.R

@@ -62,7 +62,7 @@
 #' kern_linear(1:3)
 #' kern_fbm(1:5, 1:3, gamma = 0.7)
 #'
-#' @references \url{http://phd.haziqj.ml/intro/}
+#' @references \url{https://phd.haziqj.ml/intro/}
 #'
 #' @name kernel
 #' @aliases kernels

R/Kernel_loader_helper.R

@@ -41,9 +41,6 @@ param_to_kernel <- function(param) {
   as.character(param$kernels)
 }
 
-#' @export
-.param_to_kernel <- param_to_kernel
-
 theta_to_kernel <- function(theta, object) {
   # Convert theta to vector of kernels.
   #
@@ -54,9 +51,6 @@ theta_to_kernel <- function(theta, object) {
   param_to_kernel(param)
 }
 
-#' @export
-.theta_to_kernel <- theta_to_kernel
-
 param_to_theta <- function(param, est.list, logpsi = 0) {
   # Convert param table to the theta vector. Note that theta is designed so that
   # the values are unbounded, i.e. hurst is Phi^{-1}(hurst), lengthscale is
@@ -86,9 +80,6 @@ param_to_theta <- function(param, est.list, logpsi = 0) {
        theta.omitted = theta.omitted)
 }
 
-#' @export
-.param_to_theta <- param_to_theta
-
 kernel_to_param <- function(kernels, lambda) {
   # Convert vector of kernels to a param table.
   #
@@ -115,9 +106,6 @@ kernel_to_param <- function(kernels, lambda) {
   res
 }
 
-#' @export
-.kernel_to_param <- kernel_to_param
-
 reduce_theta <- function(theta.full, est.list) {
   # The user may specify for some of the hyperparameters to not be estimated,
   # therefore theta vector should be smaller than the full set of
@@ -163,9 +151,6 @@ reduce_theta <- function(theta.full, est.list) {
        theta.drop = theta.drop)
 }
 
-#' @export
-.reduce_theta <- reduce_theta
-
 expand_theta <- function(theta.reduced, theta.drop, theta.omitted) {
   # This convertes the reduced theta vector back to the full theta vector.
   # Useful in other functions such as theta_to_param().
@@ -182,9 +167,6 @@ expand_theta <- function(theta.reduced, theta.drop, theta.omitted) {
   theta.full
 }
 
-#' @export
-.expand_theta <- expand_theta
-
 collapse_param <- function(param) {
   # Args: A param table.
   #
@@ -208,9 +190,6 @@ collapse_param <- function(param) {
   list(param = res, na = na)
 }
 
-#' @export
-.collapse_param <- collapse_param
-
 theta_to_param <- function(theta, object) {
   # Args: A vector of parameters to be optimised, including logpsi. object must
   # be either a ipriorKernel type object, or a list containing param.na,
@@ -249,9 +228,6 @@ theta_to_param <- function(theta, object) {
   param
 }
 
-#' @export
-.theta_to_param <- theta_to_param
-
 param_translator <- function(x) {
   # Helper function in theta_to_param().
   #
@@ -268,9 +244,6 @@ param_translator <- function(x) {
   "linear"
 }
 
-#' @export
-.param_translator <- param_translator
-
 correct_pearson_kernel <- function(x, which.pearson) {
   # When using theta_to_param(), unable to identify which data x uses the
   # Pearson kernel. This helper function corrects it by reading from the logical
@@ -284,9 +257,6 @@ correct_pearson_kernel <- function(x, which.pearson) {
   x
 }
 
-#' @export
-.correct_pearson_kernel <- correct_pearson_kernel
-
 kernel_translator <- function(x, y = NULL, kernel, lam.poly = 1) {
   # Used as a helper function in get_Hl() to output list of kernel
   # matrices in kernL2() and predict(). For future expansion, add new kernels
@@ -329,9 +299,6 @@ kernel_translator <- function(x, y = NULL, kernel, lam.poly = 1) {
        call. = FALSE)
 }
 
-#' @export
-.kernel_translator <- kernel_translator
-
 theta_to_collapsed_param <- function(theta, object) {
   # This is a wrapper function for theta_to_param(). It is useful to get
   # the vector of parameters directly from theta.
@@ -343,9 +310,6 @@ theta_to_collapsed_param <- function(theta, object) {
   c(collapse_param(param)$param, theta_to_psi(theta, object))
 }
 
-#' @export
-.theta_to_collapsed_param <- theta_to_collapsed_param
-
 theta_to_psi <- function(theta, object) {
   # Obtains psi from the theta vector, or if not estimated, from the
   # ipriorKernel object.
@@ -373,9 +337,6 @@ get_hyperparam <- function(x) {
   as.numeric(unlist(strsplit(x, ","))[2])
 }
 
-#' @export
-.get_hyperparam <- get_hyperparam
-
 get_polydegree <- function(x) {
   # Obtain the degree of the polynomial kernel. Note: the exported version is
   # get_degree().
@@ -392,9 +353,6 @@ get_polydegree <- function(x) {
   degree
 }
 
-#' @export
-.get_polydegree <- get_polydegree
-
 get_kernels_from_Hl <- function(x) {
   # Obtain the kernels used to generate the list of kernel matrices.
   #
@@ -404,9 +362,6 @@ get_kernels_from_Hl <- function(x) {
   sapply(x, function(x) attributes(x)$kernel)
 }
 
-#' @export
-.get_kernels_from_Hl <- get_kernels_from_Hl
-
 get_Xl.nys <- function(object) {
   # When using the Nystrom method, we calculate the kernel matrix using
   # get_Hl(Xl, Xl.nys) which produces a smaller m x n matrix. This is the helper
@@ -427,9 +382,6 @@ get_Xl.nys <- function(object) {
   }
 }
 
-#' @export
-.get_Xl.nys <- get_Xl.nys
-
 get_Hl <- function(Xl, yl = list(NULL), kernels, lambda) {
   # Obtain the list of kernel matrices. Except for polynomial kernels, these are
   # not scaled, i.e. not Hlam matrices.
@@ -442,9 +394,6 @@ get_Hl <- function(Xl, yl = list(NULL), kernels, lambda) {
   mapply(kernel_translator, Xl, yl, kernels, lambda, SIMPLIFY = FALSE)
 }
 
-#' @export
-.get_Hl <- get_Hl
-
 expand_Hl_and_lambda <- function(Hl, lambda, intr, intr.3plus, env = NULL) {
   # Helper function to expand Hl (list of kernel matrices) and lambda (scale
   # parameters) according to any interactions specification.
@@ -485,9 +434,6 @@ expand_Hl_and_lambda <- function(Hl, lambda, intr, intr.3plus, env = NULL) {
   }
 }
 
-#' @export
-.expand_Hl_and_lambda <- expand_Hl_and_lambda
-
 BlockB_fn <- function(Hl, intr, n, p) {
   # This is the function which returns the BlockBStuff required for closed-form
   # EM algorithm.

R/Utilities.R

@@ -170,9 +170,6 @@ is.ipriorKernel_cv <- function(x) {
   }
 }
 
-#' @export
-.is.ipriorKernel_cv <- is.ipriorKernel_cv
-
 #' @rdname is.iprior_x
 #' @export
 is.nystrom <- is.ipriorKernel_nys
@@ -189,9 +186,6 @@ is.categorical <- function(x) {
   !is.null(x$y.levels)
 }
 
-#' @export
-.is.categorical <- is.categorical
-
 #' Test kernel attributes
 #'
 #' Test whether an object uses a specific type of kernel.
@@ -323,12 +317,6 @@ get_y_and_levels <- function(y) {
   list(y = as.numeric(y), levels = levels(y))
 }
 
-#' @export
-.checkLevels <- get_y_and_levels
-
-#' @export
-.get_y_and_levels <- get_y_and_levels
-
 fix_call_default <- function(cl = match.call(), new.name = "iprior") {
   # Replace the default call name with a new name. When using the default call,
   # it is possible that some of the X names are blank. This fixes that too.
@@ -343,9 +331,6 @@ fix_call_default <- function(cl = match.call(), new.name = "iprior") {
   cl
 }
 
-#' @export
-.fix_call_default <- fix_call_default
-
 fix_call_formula <- function(cl = match.call(), new.name = "iprior") {
   # Replace the formula call name with a new name.
   #
@@ -356,9 +341,6 @@ fix_call_formula <- function(cl = match.call(), new.name = "iprior") {
   cl
 }
 
-#' @export
-.fix_call_formula <- fix_call_formula
-
 formula_to_xy <- function(formula, data, one.lam) {
   # Convert formula entry to y, X entry.
   #
@@ -400,9 +382,6 @@ formula_to_xy <- function(formula, data, one.lam) {
        tt = tt)
 }
 
-#' @export
-.formula_to_xy <- formula_to_xy
-
 deal_with_one.lam <- function(x, interactions) {
   # Helper function to convert list of X according to one.lam option.
   #
@@ -430,9 +409,6 @@ deal_with_one.lam <- function(x, interactions) {
   list(x = x, xname = xname)
 }
 
-#' @export
-.deal_with_one.lam <- deal_with_one.lam
-
 terms_to_xy <- function(object, newdata) {
   # Args: An ipriorKernel object.
   tt <- object$terms
@@ -452,9 +428,6 @@ terms_to_xy <- function(object, newdata) {
   list(Xl = x, y = y)
 }
 
-#' @export
-.terms_to_xy <- terms_to_xy
-
 fastSquareRoot2 <- function(x) {
   # Function to quickly find a square root of a matrix from its
   # eigendecomposition.

R/iprior-package.R

@@ -31,7 +31,11 @@
 #'
 #'   Contributors: \itemize{\item{Wicher Bergsma}}
 #'
-#' @seealso \url{http://phd.haziqj.ml/}
-#'
+#' @seealso \url{https://phd.haziqj.ml/}
 #' @keywords internal
+#' @aliases iprior-package
 "_PACKAGE"
+
+## usethis namespace: start
+## usethis namespace: end
+NULL