dont run exchange example

NEWS.md

@@ -11,7 +11,7 @@ bssm 2.0.2 (Release date: 2023-10-18)
    * Removed explicit C++ version requirement as required by new CRAN policies.
    * Removed `magrittr` dependency and switched to native pipe, leading to 
      requirement for R 4.1.0+.
-   * Added Sys.setenv("OMP_NUM_THREADS" = 2) to fix weird CRAN issues with 
+   * Added Sys.setenv("OMP_NUM_THREADS" = 2) to (partially) fix CRAN issues with 
      parallelisation on Debian.
 
 bssm 2.0.1 (Release date: 2022-05-02)

R/approx.R

@@ -31,7 +31,6 @@
 #' @export
 #' @rdname gaussian_approx
 #' @examples 
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' data("poisson_series")
 #' model <- bsm_ng(y = poisson_series, sd_slope = 0.01, sd_level = 0.1,
 #'   distribution = "poisson")

R/bssm-package.R

@@ -89,7 +89,6 @@
 #' time ts ts.union tsp tsp<- sd na.omit
 #' @useDynLib bssm
 #' @examples
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' # Create a local level model (latent random walk + noise) to the Nile
 #' # dataset using the bsm_lg function:
 #' model <- bsm_lg(Nile,
@@ -139,7 +138,6 @@ NULL
 #' \url{https://stat.fi/tup/tilastotietokannat/index_en.html}.
 #' @keywords datasets
 #' @examples
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' data("drownings")
 #' model <- bsm_ng(drownings[, "deaths"], u = drownings[, "population"],
 #'   xreg = drownings[, "summer_temp"], distribution = "poisson",
@@ -167,13 +165,14 @@ NULL
 #' Time Series Analysis by State Space Methods. Oxford University Press.
 #' https://doi.org/10.1093/acprof:oso/9780199641178.001.0001
 #' @examples
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
+#' \donttest{ # Don't test on CRAN as complains about parallelisation
 #' data("exchange")
 #' model <- svm(exchange, rho = uniform(0.97,-0.999,0.999),
 #'  sd_ar = halfnormal(0.175, 2), mu = normal(-0.87, 0, 2))
 #'
 #' out <- particle_smoother(model, particles = 500)
 #' plot.ts(cbind(model$y, exp(out$alphahat)))
+#' }
 NULL
 #' Simulated Poisson Time Series Data
 #'
@@ -191,7 +190,6 @@ NULL
 #' Scand J Statist. 1-38. https://doi.org/10.1111/sjos.12492
 #'
 #' @examples
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' # The data was generated as follows:
 #' set.seed(321)
 #' slope <- cumsum(c(0, rnorm(99, sd = 0.01)))
@@ -245,7 +243,6 @@ NULL
 #' https://doi.org/10.32614/RJ-2021-103
 #'
 #' @examples
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' # reproducing the model:
 #' data("negbin_series")
 #' # Construct model for bssm

R/ekpf_filter.R

@@ -21,7 +21,6 @@ ekpf_filter <- function(model, particles, ...) {
 #' @rdname ekpf_filter
 #' @examples
 #' \donttest{ # Takes a while
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' set.seed(1)
 #' n <- 50
 #' x <- y <- numeric(n)

R/kfilter.R

@@ -69,7 +69,6 @@ kfilter.nongaussian <- function(model, ...) {
 #' @export
 #' @examples
 #' \donttest{ # Takes a while on CRAN
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' set.seed(1)
 #' mu <- -0.2
 #' rho <- 0.7
@@ -139,7 +138,6 @@ ekf <- function(model, iekf_iter = 0) {
 #' @export
 #' @examples
 #' \donttest{ # Takes a while on CRAN
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' set.seed(1)
 #' mu <- -0.2
 #' rho <- 0.7

R/models.R

@@ -61,7 +61,6 @@ default_update_fn <- function(theta) {
 #' @return An object of class \code{ssm_ulg}.
 #' @export
 #' @examples 
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' 
 #' # Regression model with time-varying coefficients
 #' set.seed(1)

R/post_correction.R

@@ -174,7 +174,6 @@ suggest_N <- function(model, theta,
 #' @export
 #' @examples 
 #' \donttest{
-#' Sys.setenv("OMP_NUM_THREADS" = 2) # For CRAN
 #' set.seed(1)
 #' n <- 300
 #' x1 <- sin((2 * pi / 12) * 1:n)