Releases: rjdverse/rjd3filters
Releases · rjdverse/rjd3filters
v2.1.1
rjd3filters
2.1.1
Installation
Source version
From GitHub
To install this release automatically, you can use the code from the README:
# install.packages("remotes")
remotes::install_github("rjdverse/[email protected]")
From R-Universe
install.packages("rjd3filters", repos = c("https://rjdverse.r-universe.dev", "https://cloud.r-project.org"))
From file
- Download the file rjd3filters_1.3.2.tar.gz
- Install with the command line:
install.packages("rjd3filters_1.3.2.tar.gz", repos = NULL, type = "source")
Binary versions
- Download the binary version of the package related to your R version (so the file rjd3filters_1.3.2_R_X.X.X.zip with X.X.X your version of R):
# For example with R 4.2.3
temp_path <- file.path(tempdir(), "rjd3filters_2.1.1.zip")
download.file(
url = "https://github.com/rjdverse/rjd3filters/releases/download/v2.1.1/rjd3filters_1.3.2_R_4.2.3.zip",
destfile = temp_path
)
install.packages(temp_path, repos = NULL, type = "binary")
Updates
Changed
cross_validation()
function renamed tocve()
,cross_validation()
is now deprecated.- New .jar files added (related to v2.2.0)
Added
-
New functions to compute functions to compute diagnostics and goodness of fit of filtered series: cross validation (
cv()
) and cross validate estimate (cve()
), leave-one-out cross validation estimate (loocve
), CP statistic (cp()
) and Rice's T statistics (rt()
). -
New function
confint_filter()
to compute confidence intervals for filtered series. -
New function
is.finite_filters()
. -
New parameter
zero_as_na
incbind.moving_average
, boolean indicating if trealing and leading zeros added to have a matrix form should be replaced byNA
.