DrNickRedfern

scaleFUN <- function(x) sprintf("%.1f", x)

DrNickRedfern

.csl-entry {
  margin-bottom: 10px;
}

DrNickRedfern

loglik2AIC <- function(l, k){round((-2 * l) + (2 * k), 3)}

DrNickRedfern

trimean <- function(x, p = 0.25, a = 0.25){
  q <- Hmisc::hdquantile(x, probs = c(p, 0.5, 1-p), na.rm = TRUE, names = FALSE)
  tm <- (a * q[1]) + ((1 - (2 * p)) * q[2]) + (a * q[3])
  return(tm)
}

DrNickRedfern

cmd <- function(x){median(abs(x - median))/median(x)}

DrNickRedfern

q_summary <- function (x) {
  h <- Hmisc::hdquantile(x, probs = seq(0.125, 0.875, 0.125), na.rm = TRUE, names = FALSE, se = FALSE, weights = FALSE)
  med = h[4]; iqr = h[6] - h[2]
  skew = (h[2] + h[6] - (2 * h[4]))/iqr; kurt = ((h[7] - h[5]) + (h[3] - h[1]))/iqr
  qcd = (iqr)/(h[6] + h[2])
  out <- list(med, iqr, skew, kurt, qcd)
  names(out) <- c("median", "IQR", "skewness", "kurtosis", "quatile coefficient of dispersion")
  return(out)
}

DrNickRedfern

loessggplot <- function(x, low = 0.1, high = 0.9, step = 0.01, title = "", ticks = 0.1){ 
  
  n <- length(x)
  t <- cumsum(x); t <- 100*t/max(t)  # normalize the running time to percent
  
  # Create an empty data fame to store the results of the for loop
  df <- data.frame() 
  
  # Loop over the sequence of spans for the loess smoothers and store the result
  for(s in seq(low, high, step)) { 

DrNickRedfern

loessggplot(backstage, low = 0.1, high = 0.9, step = 0.01, title = "Backstage (1919)", ticks = 0.1)

DrNickRedfern

# Check the class of the output of seewave::acoustat()
class(insidious_chapter_3_nape)

## [1] "matrix" "array"

DrNickRedfern

function (raw_values, title = "Syuzhet Plot", legend_pos = "top", 
  lps = 10, window = 0.1) 
{
  wdw <- round(length(raw_values) * window)
  rolled <- rescale(zoo::rollmean(raw_values, k = wdw, fill = 0))
  half <- round(wdw/2)
  rolled[1:half] <- NA
  end <- length(rolled) - half
  rolled[end:length(rolled)] <- NA
  trans <- get_dct_transform(raw_values, low_pass_size = lps,