Running examples in 'mgcv-Ex.R' failed
The error most likely occurred in:

> ### Name: shash
> ### Title: Sinh-arcsinh location scale and shape model family
> ### Aliases: shash
> 
> ### ** Examples
> 
> 
> ###############
> # Shash dataset
> ###############
> ##  Simulate some data from shash
> set.seed(847)
> n <- 1000
> x <- seq(-4, 4, length.out = n)
> 
> X <- cbind(1, x, x^2)
> beta <- c(4, 1, 1)
> mu <- X %*% beta 
> 
> sigma =  .5+0.4*(x+4)*.5            # Scale
> eps = 2*sin(x)                      # Skewness
> del = 1 + 0.2*cos(3*x)              # Kurtosis
> 
> dat <-  mu + (del*sigma)*sinh((1/del)*asinh(qnorm(runif(n))) + (eps/del))
> dataf <- data.frame(cbind(dat, x))
> names(dataf) <- c("y", "x")
> plot(x, dat, xlab = "x", ylab = "y")
> 
> ## Fit model
> fit <- gam(list(y ~ s(x), # <- model for location 
+                   ~ s(x),   # <- model for log-scale
+                   ~ s(x),   # <- model for skewness
+                   ~ s(x, k = 20)), # <- model for log-kurtosis
+            data = dataf, 
+            family = shash, # <- new family 
+            optimizer = "efs")
> 
> ## Plotting truth and estimates for each parameters of the density 
> muE <- fit$fitted[ , 1]
> sigE <- exp(fit$fitted[ , 2])
> epsE <- fit$fitted[ , 3]
> delE <- exp(fit$fitted[ , 4])
> 
> par(mfrow = c(2, 2))
> plot(x, muE, type = 'l', ylab = expression(mu(x)), lwd = 2)
> lines(x, mu, col = 2, lty = 2, lwd = 2)
> legend("top", c("estimated", "truth"), col = 1:2, lty = 1:2, lwd = 2)
> 
> plot(x, sigE, type = 'l', ylab = expression(sigma(x)), lwd = 2)
> lines(x, sigma, col = 2, lty = 2, lwd = 2)
> 
> plot(x, epsE, type = 'l', ylab = expression(epsilon(x)), lwd = 2)
> lines(x, eps, col = 2, lty = 2, lwd = 2)
> 
> plot(x, delE, type = 'l', ylab = expression(delta(x)), lwd = 2)
> lines(x, del, col = 2, lty = 2, lwd = 2)
> 
> ## Plotting true and estimated conditional density
> par(mfrow = c(1, 1))
> plot(x, dat, pch = '.', col = "grey", ylab = "y", ylim = c(-35, 70))
> for(qq in c(0.001, 0.01, 0.1, 0.5, 0.9, 0.99, 0.999)){
+   est <- fit$family$qf(p=qq, mu = fit$fitted)
+   true <- mu + (del * sigma) * sinh((1/del) * asinh(qnorm(qq)) + (eps/del))
+   lines(x, est, type = 'l', col = 1, lwd = 2)
+   lines(x, true, type = 'l', col = 2, lwd = 2, lty = 2)
+ }
> legend("topleft", c("estimated", "truth"), col = 1:2, lty = 1:2, lwd = 2)
> 
> #####################
> ## Motorcycle example
> #####################
> 
> # Here shash is overkill, in fact the fit is not good, relative
> # to what we would get with mgcv::gaulss
> library(MASS)
> 
> b <- gam(list(accel~s(times, k=20, bs = "ad"), ~s(times, k = 10), ~1, ~1),
+          data=mcycle, family=shash)