From 25b733e5916a5fa37a55dc68ce47c8dce2e48bd0 Mon Sep 17 00:00:00 2001 From: Jonathan Berrisch Date: Tue, 9 Jan 2024 16:40:35 +0100 Subject: [PATCH] Prepare release --- DESCRIPTION | 4 ++-- R/splines.R | 2 +- man/make_hat_mats.Rd | 2 +- vignettes/class.Rmd | 4 ++-- 4 files changed, 6 insertions(+), 6 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 96b1339..775d55f 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,8 +1,8 @@ Package: profoc Type: Package Title: Probabilistic Forecast Combination Using CRPS Learning -Version: 1.2.2.9000 -Date: 2023-08-28 +Version: 1.3.0 +Date: 2024-01-09 Authors@R: c( person(given = "Jonathan", family = "Berrisch", diff --git a/R/splines.R b/R/splines.R index 8a719fd..074f5e2 100644 --- a/R/splines.R +++ b/R/splines.R @@ -137,7 +137,7 @@ make_basis_mats <- function(x, # Splines basis #' @param nonc Beta distribution noncentrality parameter #' @param tailw Tailweight #' @param deg Degree of splines -#' @param ndiff Sets the degree of the differencing matrix for creaing +#' @param ndiff Sets the degree of the differencing matrix for creating #' the penalty #' @param lambda Penalty parameter (higher values lead to higher penalty) #' @param periodic Create periodic penalty diff --git a/man/make_hat_mats.Rd b/man/make_hat_mats.Rd index 5db4b82..2dd15e6 100644 --- a/man/make_hat_mats.Rd +++ b/man/make_hat_mats.Rd @@ -34,7 +34,7 @@ make_hat_mats( \item{deg}{Degree of splines} -\item{ndiff}{Sets the degree of the differencing matrix for creaing +\item{ndiff}{Sets the degree of the differencing matrix for creating the penalty} \item{lambda}{Penalty parameter (higher values lead to higher penalty)} diff --git a/vignettes/class.Rmd b/vignettes/class.Rmd index ba0abc0..b373f09 100644 --- a/vignettes/class.Rmd +++ b/vignettes/class.Rmd @@ -19,7 +19,7 @@ vignette: > All major parts of `online()` are implemented in C++ for speed. Usually, this comes at the cost of flexibility. However, the profoc package exposes a C++ class `conline` that allows you to gain fine grained control over objects. -`online()` wrapps this class and provides a convenient interface for the most +`online()` wraps this class and provides a convenient interface for the most common use cases. However, if you need to alter object initialization (i.e. provide custom basis / hat matrices for smoothing) you can use the C++ class directly from R. This vignette shows how to do this. @@ -75,7 +75,7 @@ tau <- 1:P / (P + 1) model$tau <- tau ``` -The experts array is a bit more complicated. C++ expects us to pass a list of arrays. Thereby, the list itself must have dimension `Tx1` and the elements of the list (the arrays) `D x P x K`. For convenience we can use `init_experts_list()` to create such a list from our experts array. Note that we must pass the true observations as well. They are used to detect wether the data is univariate (`T x 1` matrix) or multivariate (`T x D` matrix). +The experts array is a bit more complicated. C++ expects us to pass a list of arrays. Thereby, the list itself must have dimension `Tx1` and the elements of the list (the arrays) `D x P x K`. For convenience we can use `init_experts_list()` to create such a list from our experts array. Note that we must pass the true observations as well. They are used to detect whether the data is univariate (`T x 1` matrix) or multivariate (`T x D` matrix). ```{r} experts_list <- init_experts_list(experts, y)