Created
July 28, 2024 14:55
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R function for fitting a normal mixture model to exit velocities for balls in play for a specific baseball hitter.
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| fit_norm_mix_model <- function(pname, statcast){ | |
| require(dplyr) | |
| require(LearnBayes) | |
| library(magrittr) | |
| logpost <- function(theta, y){ | |
| mu1 <- theta[1] | |
| sigma1 <- exp(theta[2]) | |
| mu2 <- theta[3] | |
| sigma2 <- exp(theta[4]) | |
| p <- exp(theta[5]) / (1 + exp(theta[5])) | |
| sum(log(p * dnorm(y, mu1, sigma1) + | |
| (1 - p) * dnorm(y, mu2, sigma2))) | |
| } | |
| invlogit <- function(y){ | |
| exp(y) / (1 + exp(y)) | |
| } | |
| statcast |> | |
| filter(type == "X", | |
| player_name == pname) |> | |
| filter(is.na(launch_speed) == FALSE) |> | |
| pull(launch_speed) -> y_AB | |
| y1 <- y_AB[y_AB < median(y_AB)] | |
| y2 <- y_AB[y_AB > median(y_AB)] | |
| theta0 <- c(mean(y1), log(sd(y1)), | |
| mean(y2), log(sd(y2)), 0) | |
| laplace(logpost, theta0, y_AB) |> | |
| extract2(1) -> Mode | |
| data.frame(player_name = pname, | |
| mu1 = Mode[1], log_sd1 = Mode[2], | |
| mu2 = Mode[3], log_sd2 = Mode[4], | |
| logit_p = Mode[5]) |> | |
| mutate(sd1 = exp(log_sd1), | |
| sd2 = exp(log_sd2), | |
| p = invlogit(logit_p)) |> | |
| select(player_name, mu1, sd1, mu2, sd2, p) | |
| } |
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