noamross

#' Create a random effect basis with integers rather than factors
#' @import mgcv
#' @export
smooth.construct.re2.smooth.spec <- function (object, data, knots) {
  if (!is.null(object$id))
    stop("random effects don't work with ids.")
  if(any(sapply(data, is.numeric))) data <- lapply(data, as.factor)   ## <-- All I did was this (and below)
  form <- as.formula(paste("~", paste(object$term, collapse = ":"),
                           "-1"))
  object$X <- model.matrix(form, data)

noamross

#' Function to partition unequal sized groups into shards of similar size.
#'
#' Based on the greedy algorithm described in [The Wikipedia article on the
#' the partitioning problem](https://en.wikipedia.org/wiki/Partition_problem#The_greedy_algorithm)
#'
#' @param groups_vector An integer vector of group ids, such as a group ID
#'   column in a data frame
#' @param n_shards The number of shards to split groups up into
#' @examples
#' n_groups <- 200

noamross

Keybase proof

I hereby claim:

• I am noamross on github.
• I am noamross (https://keybase.io/noamross) on keybase.
• I have a public key ASB-BxfY2ry-bqcNtfdHGtsrS2Xwb0kBX2i_fgE1znBsSQo

To claim this, I am signing this object:

noamross

---
title: "test"
output:
  flexdashboard::flex_dashboard:
    orientation: rows
runtime: shiny
---

```{r setup, include = FALSE}
library(shiny)

noamross

-- a lua filter for panodoc
-- run pandoc your_word_doc.docx --track-change=all -t markdown --lua-filter=criticmarkup.lua
-- TODO: Detect substitutions in adjacent insertion/deletions
-- TODO: capture whole comment hightlight rather than just start point of comment
function Span(elem)
  if elem.classes[1] and elem.classes[1] == "insertion" then
    local opener = { pandoc.RawInline(FORMAT, "{++ ") }
    local closer = { pandoc.RawInline(FORMAT, " ++}") }
    return opener .. elem.content .. closer
  elseif

noamross

---
title: "Test RVG pptx"
output:
  powerpoint_presentation:
    keep_md: TRUE
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
library(ggplot2)

noamross

library(tidyverse)
library(gganimate)
library(mgcv)
library(mvtnorm)

# Fit a GAM to the data
mod <- gam(hp ~ s(mpg), data=mtcars, method="REML")

# Get the linear prediction matrix
newdat = data.frame(

noamross

#!/bin/bash

# Put this file somewhere and run  
# export EDITOR=/path/to/rs_term_editor.sh
# export GIT_EDITOR=/path/to/rs_term_editor.sh 
# There's probably some way to set thes e in my profile to only run
# when RSTUDIO=1 

### Set initial time of file
LTIME=`stat -f "%m" $1`

noamross

# Copyright 2018 Noam Ross
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all

noamross

library(rtweet) #rtweet API creds should already be set up
library(dplyr)
library(ggplot2)
library(hrbrthemes)
library(tidytext)
library(lubridate)

hbt <- get_timeline("hrbrmstr", n=3200)

hbt2 <- hbt %>%