WalkerHarrison

library(expm)
p <- 4
mt <- rep(1, p)
G <- diag(p); G[1:(p-1), 2:p] <- G[1:(p-1), 2:p] + diag(p-1);
F <- c(1, rep(0, p-1))

print(G); print(mt); print(F)

k <- 5
G %^% k

WalkerHarrison

library(expm)

###### polynomial ######

p <- 4
mt <- rep(1, p)
G <- diag(p); G[1:(p-1), 2:p] <- G[1:(p-1), 2:p] + diag(p-1);
F <- c(1, rep(0, p-1))

print(G); print(mt); print(F)

WalkerHarrison

strapz <- list()
k <- 10
for (i in 1:k){
  meps.bs <- meps %>% sample_n(nrow(.), replace = TRUE)
  prop.score.fit <- multinom(race ~ . - healthExp, data = meps.bs, maxit = 200,
                             trace = FALSE, model = TRUE)
  strapz[[i]] <- prop.score.fit
}

save(strapz, file = "strapz.Rdata")

WalkerHarrison

git clone https://github.com/jeetsukumaran/Syrupy
cd Syrupy
python setup.py install
syrupy.py -m 20

WalkerHarrison

# pitch/play data scraped with pitchRx

pitches18 %>% 
  filter(type == 'X', 
         pitch_type == "FF") %>%
  mutate(TB = case_when(
    event == "Single" ~    1,
    event == "Double" ~    2,
    event == "Triple" ~    3,
    event == "Home Run" ~  4,

WalkerHarrison

library(tidyverse)
library(ggvis)

## this column needs to be unique for each row (primary key)!
mtcars$url <- paste0("https://en.wikipedia.org/wiki/", 1:nrow(mtcars))

mtcars %>%
  ggvis(~mpg, ~hp) %>%
  layer_points(size := 50, size.hover := 200,
               fillOpacity := 0.4, fillOpacity.hover := 0.7,