carlbfrederick

#' Calculates rolling weeks backward from the end_date.
#' 
#' The purpose is to group a vector of dates into 7 day weeks
#' backward in time. For example, if the end date was 2020-06-09, 
#' the days 2020-06-03 through 2020-06-09 would be one week,
#' 2020-05-27 through 2020-06-02 would be another week, 2020-05-20
#' through 2020-05-26 another and so on. The function will work even
#' if the vector of dates is missing one or more dates in the series.
#'
#' @param date_vector the vector of dates to group into weeks. Must be

carlbfrederick

---
title: "Sample Lato .Rmd"
author: "Carl Frederick"
date: "11/12/2018"
mainfont: Lato
output: 
  pdf_document: 
    latex_engine: xelatex

---

carlbfrederick

library(babynames)
library(tidyverse)

set.seed(8746)

snames <- sample(babynames$name, 14)
unames <- snames[11:14]
snames <- snames[1:10]

Agency1 <- data_frame(Person = c(sample(snames, 5), unames[1]),

carlbfrederick

#'dataMaid_cleanPlot.R
#'
#'These functions makes the default graphics prettier/easier to read:
#'
#'  1. Minimal Theme
#'  2. Angled Axis Text
#'
#' @example 

cleanPlotHelper <- function(data, vnam, sideways) {

carlbfrederick

#'dataMaid_isIDvar.R
#'
#'This function identifies "Key" and similar variables and stops dataMaid::makeDataReport from creating
#'visualizations and/or other inappropriate summaries.  Instead it outputs a table with minimal information 
#'(see https://cran.rstudio.com/web/packages/dataMaid/vignettes/extending_dataMaid.html for inspiration).
#'
#' @example
#' makeDataReport(toyData, output = "html", 
#'                preChecks = c("isKey", "isSingular", "isSupported", "isIDvar"))

carlbfrederick

library(tidyverse)
library(DiagrammeR)

#Get package functions ----

ls_fcns <- function(pkg) {
  fcns <- unclass(lsf.str(envir = asNamespace(pkg), all = TRUE))
  return(as.character(fcns))
}

carlbfrederick

#Internal Functions
MYagsurv <- function(y, x, wt, risk, survtype=3, vartype=3) {
    nvar <- ncol(as.matrix(x))
    status <- y[, ncol(y)]
    dtime <- y[, ncol(y) - 1]
    death <- (status == 1)
    time <- sort(unique(dtime))
    nevent <- as.vector(rowsum(wt * death, dtime))
    ncens <- as.vector(rowsum(wt * (!death), dtime))
    wrisk <- c(wt * risk)  #Had to add c() to remove the dimnames so that the multiplication later would work