Nan Xiao nanxstats

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First release

Proof read Title: and Description: and ensure they are informative
Check that all exported functions have @returns and @examples
Check that Authors@R: includes a copyright holder (role 'cph')
Review extrachecks
usethis::use_cran_comments() (optional)

Prepare for release

First release:

usethis::use_cran_comments()
Proof read Title: and Description:
Check that all exported functions have @returns and @examples
Check that Authors@R: includes a copyright holder (role 'cph')
Check licensing of included files
Review https://github.com/DavisVaughan/extrachecks

Prepare for release:

TensorFlow Installation

I have to admit that it is painful to install TensorFlow, especially when you need a specific version. That's why I took some notes.

My general experience is that the pip approach has many potential issues on its path, mostly due to the dependency version issues from NVIDIA's libraries. The conda approach is much easier as it bundles everything.

This is written on 2020-11-27. The applicability might change in the future.

	fileInputArea <- function(inputId, label, multiple = FALSE, accept = NULL,
	width = NULL, buttonLabel = "Browse...", placeholder = "No file selected") {
	restoredValue <- restoreInput(id = inputId, default = NULL)

	# Catch potential edge case - ensure that it's either NULL or a data frame.
	if (!is.null(restoredValue) && !is.data.frame(restoredValue)) {
	warning("Restored value for ", inputId, " has incorrect format.")
	restoredValue <- NULL
	}

	switchInput <- function(inputId, label, value = FALSE, disabled = FALSE, width = NULL) {
	value <- shiny::restoreInput(id = inputId, default = value)
	inputTag <- htmltools::tags$input(id = inputId, type = "checkbox", role = "switch", class = "form-check-input")
	if (!is.null(value) && value) {
	inputTag$attribs$checked <- NA
	}
	if (!is.null(disabled) && disabled) {
	inputTag$attribs$disabled <- NA
	}
	htmltools::tags$div(

	# Generate mock data -----------------------------------------------------------
	set.seed(42)
	k <- 100
	df <- data.frame(
	title = unlist(purrr::map2(
	.x = stringr::word(stringi::stri_rand_lipsum(k), start = 1, end = 10),
	.y = rep("#", k),
	.f = function(.x, .y) as.character(htmltools::tags$a(.x, href = .y))
	)),
	time = as.POSIXct(unlist(

	library(knitr)
	library(htmltools)
	library(webshot2)

	df <- mtcars[2:7, c("mpg", "disp", "drat", "wt", "qsec")]
	rownames(df) <- NULL
	colnames(df) <- NULL

	tnum <- function(font, title, output) {
	tags$html(

	library("shiny")
	library("ggplot2")

	ui <- fluidPage(
	plotOutput("plot_responsive")
	)

	server <- function(input, output, session) {
	output$plot_responsive <- renderImage(
	{

	# https://nanx.me/blog/post/bayesian-lasso-with-greta/

	# generate synthetic data ------------------------------------------------------

	library("msaenet")

	n <- 500
	p <- 1000
	pnz <- 10

Nan Xiao nanxstats

TensorFlow Installation

GPU Driver