Type:	Package
Title:	'rmarkdown' Extension for Formatted 'RJDemetra' Outputs
Version:	0.2.2
Description:	Functions to have nice 'rmarkdown' outputs of the seasonal and trading day adjustment models made with 'RJDemetra'.
SystemRequirements:	Java (>= 8)
Depends:	R (≥ 3.1.1), RJDemetra
Imports:	knitr, kableExtra, magrittr
License:	EUPL version 1.1 | EUPL version 1.2 [expanded from: EUPL]
URL:	https://github.com/AQLT/rjdmarkdown
BugReports:	https://github.com/AQLT/rjdmarkdown/issues
Encoding:	UTF-8
RoxygenNote:	7.2.3
VignetteBuilder:	knitr
Suggests:	rmarkdown, ggdemetra
NeedsCompilation:	no
Packaged:	2023-10-04 16:43:35 UTC; alainquartierlatente
Author:	Alain Quartier-la-Tente [aut, cre]
Maintainer:	Alain Quartier-la-Tente <alain.quartier@yahoo.fr>
Repository:	CRAN
Date/Publication:	2023-10-04 19:40:01 UTC

Create and render 'rmarkdown' file

Description

Function to create a 'rmarkdown' file with all the output and render it

Usage

create_rmd(
  x,
  output_file,
  output_format = "pdf_document",
  preprocessing_fun = print_preprocessing,
  decomposition_fun = print_decomposition,
  diagnostics_fun = print_diagnostics,
  title = "Seasonal adjustment summary",
  knitr_chunk_opts = list(fig.pos = "h", echo = FALSE, results = "asis", fig.cap =
    "S-I Ratio"),
  ...
)

## S3 method for class 'SA'
create_rmd(
  x,
  output_file,
  output_format = "pdf_document",
  preprocessing_fun = print_preprocessing,
  decomposition_fun = print_decomposition,
  diagnostics_fun = print_diagnostics,
  title = "Seasonal adjustment summary",
  knitr_chunk_opts = list(fig.pos = "h", echo = FALSE, results = "asis", fig.cap =
    "S-I Ratio"),
  ...
)

## S3 method for class 'jSA'
create_rmd(
  x,
  output_file,
  output_format = "pdf_document",
  preprocessing_fun = print_preprocessing,
  decomposition_fun = print_decomposition,
  diagnostics_fun = print_diagnostics,
  title = "Seasonal adjustment summary",
  knitr_chunk_opts = list(fig.pos = "h", echo = FALSE, results = "asis", fig.cap =
    "S-I Ratio"),
  ...
)

## S3 method for class 'workspace'
create_rmd(
  x,
  output_file,
  output_format = "pdf_document",
  preprocessing_fun = print_preprocessing,
  decomposition_fun = print_decomposition,
  diagnostics_fun = print_diagnostics,
  title = "Seasonal adjustment summary",
  knitr_chunk_opts = list(fig.pos = "h", echo = FALSE, results = "asis", fig.cap =
    "S-I Ratio"),
  ...
)

## S3 method for class 'multiprocessing'
create_rmd(
  x,
  output_file,
  output_format = "pdf_document",
  preprocessing_fun = print_preprocessing,
  decomposition_fun = print_decomposition,
  diagnostics_fun = print_diagnostics,
  title = "Seasonal adjustment summary",
  knitr_chunk_opts = list(fig.pos = "h", echo = FALSE, results = "asis", fig.cap =
    "S-I Ratio"),
  ...,
  workspace
)

## S3 method for class 'sa_item'
create_rmd(
  x,
  output_file,
  output_format = "pdf_document",
  preprocessing_fun = print_preprocessing,
  decomposition_fun = print_decomposition,
  diagnostics_fun = print_diagnostics,
  title = "Seasonal adjustment summary",
  knitr_chunk_opts = list(fig.pos = "h", echo = FALSE, results = "asis", fig.cap =
    "S-I Ratio"),
  ...,
  workspace
)

Arguments

Examples

ipi <- RJDemetra::ipi_c_eu[, "FR"]
jsa_x13 <- RJDemetra::jx13(ipi)

output_file <- tempfile(fileext = ".Rmd")
create_rmd(jsa_x13, output_file, output_format = "pdf_document")
# To directly open the pdf:
browseURL(sub(".Rmd",".pdf", output_file, fixed = TRUE))


# To create a pdf from a workspace:
jsa_ts <- jtramoseats(ipi)
wk <- new_workspace()
mp <- new_multiprocessing(wk, "sa1")
add_sa_item(wk, "sa1", jsa_x13, "X13")
add_sa_item(wk, "sa1", jsa_ts, "TramoSeats")

# It's important to compute the workspace to be able
# to import the models
compute(wk)

output_file <- tempfile(fileext = ".Rmd")
create_rmd(wk, output_file, 
           output_format = c("pdf_document", "html_document"),
           output_options = list(toc = TRUE,
                                 number_sections = TRUE))
# To open the file:
browseURL(sub(".Rmd",".pdf", output_file, fixed = TRUE))
browseURL(sub(".Rmd",".html", output_file, fixed = TRUE))

Print the decomposition

Description

Function to print the decomposition model

Usage

print_decomposition(
  x,
  format = knitr::opts_knit$get("rmarkdown.pandoc.to"),
  plot = TRUE,
  digits = 3,
  decimal.mark = getOption("OutDec"),
  booktabs = TRUE,
  ...
)

Arguments

Examples

ipi <- RJDemetra::ipi_c_eu[, "FR"]

jsa_x13 <- RJDemetra::jx13(ipi)
print_decomposition(jsa_x13, format = "latex")


sa_ts <- RJDemetra::jtramoseats(ipi)
print_decomposition(sa_ts, format = "html")

Print the diagnostics

Description

Function to print diagnostics tests on the quality of the pre-processing and the decomposition

Usage

print_diagnostics(
  x,
  format = knitr::opts_knit$get("rmarkdown.pandoc.to"),
  signif.stars = TRUE,
  tests = c("mean", "skewness", "kurtosis", "ljung box",
    "ljung box (residuals at seasonal lags)", "ljung box (squared residuals)",
    "qs test on sa", "qs test on i", "f-test on sa (seasonal dummies)",
    "f-test on i (seasonal dummies)", "Residual seasonality (entire series)",
    "Residual seasonality (last 3 years)", "f-test on sa (td)", "f-test on i (td)"),
  digits = 3,
  decimal.mark = getOption("OutDec"),
  booktabs = TRUE,
  ...
)

Arguments

Examples

ipi <- RJDemetra::ipi_c_eu[, "FR"]

jsa_x13 <- RJDemetra::jx13(ipi)
print_diagnostics(jsa_x13, format = "latex")


sa_ts <- RJDemetra::tramoseats(ipi)
print_diagnostics(sa_ts, format = "html")

Print the pre-processing model

Description

Function to print the pre-processing model

Usage

print_preprocessing(
  x,
  format = knitr::opts_knit$get("rmarkdown.pandoc.to"),
  signif.stars = TRUE,
  digits = 3,
  decimal.mark = getOption("OutDec"),
  booktabs = TRUE,
  summary = TRUE,
  likelihood = TRUE,
  arima = TRUE,
  regression = TRUE,
  ...
)

Arguments

Examples

ipi <- RJDemetra::ipi_c_eu[, "FR"]

sa_x13 <- RJDemetra::jx13(ipi)
print_preprocessing(sa_x13, format = "latex")


sa_ts <- RJDemetra::tramoseats(ipi)
print_preprocessing(sa_ts, format = "html")