GarrettMooney

library(purrr)

data_dir <- here::here()
base_url <- "http://www.pjm.com"
url <- sprintf("%s/pub/operations/hist-meter-load", base_url)
years <- 1993L:2018L

# check for robots.txt
robotstxt::get_robotstxt(base_url)

GarrettMooney

#' description:
#' Get the AUC for the {validation,test} data set for a given model.
#' usage:
#' list(best_dl, best_gbm) %>% map_dbl(h2o_auc_v) %>% set_names('DL AUC', 'GBM AUC')
#' list(best_dl, best_gbm) %>% map_dbl(h2o_auc_t) %>% set_names('DL AUC', 'GBM AUC')
library(h2o)
library(purrr)
h2o_auc_t <- compose(h2o.auc, partial(h2o.performance, newdata = test))
h2o_auc_v <- compose(h2o.auc, partial(h2o.performance, newdata = valid))

GarrettMooney

Multiclass classifier
----

```{r, include=FALSE}
knitr::opts_chunk$set(
  comment = "#>",
  collapse = TRUE,
  cache = TRUE,
  echo = FALSE,
  out.width = "70%",

GarrettMooney

Spike and Slab Prior
----
```{r, message=FALSE}
library(magrittr)
```

```{r}
prior_plot <- function(lower, upper, sigma, ...) {
  seq(lower, upper, l=100) %>% plot(., dnorm(., 0, sigma))
  abline(v= 0, lty = 2, col = "red")

GarrettMooney

compiler::enableJIT(0)
compiler::enableJIT(0)

rustinr::rust(code = '
// #[rustr_export]
pub fn fib_rust(a : i32) -> RResult<f64>{
    let mut first  = 0.0;
    let mut second = 1.0;
    let mut third  = 0.0;
    for _ in 0..a {

GarrettMooney

library(rvest)
library(purrr)
library(stringr)

url <- "http://ellisp.github.io/blog/2016/11/06/forecastxgb"
robotstxt::get_robotstxt(url)

url %>%
  read_html() %>% html_nodes("span") %>% html_text() %>%
  reduce(., str_c) %>%

GarrettMooney

library(purrr)

# two regressions
lm_fit <- lm(mpg ~ wt + cyl, data = mtcars)
bayes_fit <- rstanarm::stan_glm(mpg ~ wt + cyl, data = mtcars)

# design matrix [32 x 3]
X <- model.matrix(lm_fit)

# coefficient matrix [3 x 2]

GarrettMooney

library(gistr)

# create
gist_create(files='../create_gist.R', 
            description='Create gist via R.')

# update
gists(what = "minepublic")[[1]] %>%
  update_files('../create_gist.R') %>%
  update()

GarrettMooney

library(tidyverse)

y <- as.matrix(mtcars$mpg)
X <- model.matrix(mpg ~ ., mtcars)

# linear regression
solve(crossprod(X)) %*% t(X) %*% y
solve(crossprod(X) + 0 * diag(rep(1, ncol(X)))) %*% t(X) %*% y

# ridge regression

GarrettMooney

.First <- function() {

  # set TZ if unset
  if (is.na(Sys.getenv("TZ", unset = NA)))
    Sys.setenv(TZ = "America/New_York")

  # bail if revo R
  if (exists("Revo.version"))
    return()