library(forecast)
data<-c(2,3,2,3,2,3)

forecast(Arima(data,order=c(0,0,0)))$mean
 [1] 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5

forecast(Arima(data,order=c(0,0,0), lambda=0))$mean
[1] 2.44949 2.44949 2.44949 2.44949 2.44949 2.44949 2.44949 2.44949 2.44949 2.44949

library(forecast)

fit <- auto.arima(AirPassengers, lambda=0)
fc <- forecast(fit, h=50, level=95)
fvar <- ((BoxCox(fc$upper,fit$lambda)-BoxCox(fc$lower,fit$lambda))/qnorm(0.975)/2)^2
plot(fc)
fc$mean <- fc$mean * (1 + 0.5*fvar)
lines(fc$mean,col='red')

fit <- auto.arima(AirPassengers, lambda=0.2)
fc <- forecast(fit, h=50, level=95)
fvar <- ((BoxCox(fc$upper,fit$lambda)-BoxCox(fc$lower,fit$lambda))/qnorm(0.975)/2)^2
plot(fc)
fc$mean <- fc$mean * (1 + 0.5*fvar*(1-fit$lambda)/(fc$mean)^(2*fit$lambda))
lines(fc$mean,col='red')