Submitted 3.3 to CRAN and received a NOTE concerning documentation
files for the GDPCI data set, referencing the Guide to the
National Income and Product Accounts of the United States (NIPA).
Updated source from http://www.bea.gov/national/pdf/nipaguid.pdf to
https://www.bea.gov/resources/methodologies/nipa-handbook
The knitr maintainer decided to remove
rmarkdown as a dependency, so the vignette build now fails.
It must be added, or else CRAN will remove the package by
2021-05-14.
Updated all data sets.
SP500 data includes more variables from Robert
Schiller’s data set for U.S. Stock Markets 1871-2021.
Update data for FEDFUNDS, GS10,
PAYEMS, UNRATENSA, and SP500.
Content edits and cleanup of vignettes.
These included, removing the redundant call to
library(xts) as it has been moved to Depends
instead of merely Suggests, as documented in 0.3-0 below.
Thus, calling neverhpfilter includes it.
While the vignette builder uses the knitr package, I was
also loading the knitr package to access the
kable function for tables. Testing was going fine, but then
knitr inexplicably began throwing a variety of differing
errors across Linux and Windows builds. This appears to be due to
Suggested packages it couldn’t import, so removing calls to
knitr in the vignette was an easy place to begin reducing
the area of an unknown attack surface. In the modern era, regardless of
the original error, any opportunity to reduce dependencies seems the
most sensible approach as ever increasing dependency sprawl has bestowed
upon R package maintainers a constant, exponentially growing, attack
surface.
The decision to remove knitr::kable from vignettes was
also an aesthetic one. In my experience, tables remain an important
device for graphic displays of information. While knitr’s html format
appears clean at first, closer inspection reveals the undesirable trait
of fitting tables to full page width regardless of the number of columns
to display. On deeper reflection, I view this as a bug, as it produces
the undesirable side effect of too much white space for the reader’s eye
to traverse when comparing numbers across columns.
Printing the raw output of an xts or
data.frame objects keeps columns compact, allowing for
clearer visual comparison. The raw output also better communicates to
our reader the table was created as a result of some computational
process. Plus, in an increasingly sophisticated digital world of Ux,
these raw outputs look increasingly, unique, computationally cool, and
clean. They serve as a reminder of the objective and scientific nature
we strive for in our endeavors.
Feature, updated data through January 2020.
New vignette Getting started reworks and replaces
Additional examples.
Increased R version dependency to (>= 3.5.0) for the
.Rdata files.
Moved from testtthat to tinytest, and wrote
additional function unit tests and data unit tests.
Moved xts and zoo from imports to depends.
Now xts (>= 0.11-0) and zoo (>=
1.8-0)
Bug fix, see issue-1 here.
Updated data from original to roughly Q2 2019.
Consolidated into two functions. yth_glm remains
unchanged, while yth_filter has been given an
output argument to specify the return of specific series.
This feature eliminates the need for yth_cycle and
yth_trend, which were helpful when applying the function to
multiple data sets. Done so at the strong suggestion of
CRAN, and has ultimatly proven a good idea.
Additional data sets have been added to replicate most all of Hamilton’s table 2.
The “Reproducing Hamilton” vignette has been expanded and content has been edited for clarity.
First complete version. Has four functions yth_glm,
yth_filter, yth_cycle, and
yth_trend. Three data sets are included to reproduce part
of Hamilton’s work. They are GDPC1, PAYEMS,
and Hamilton_table_2. A vignette titled “Reproducing
Hamilton” illustrated the work and shows users how to implement
functions.