The following is the complete R code:
# Time series data kings <- scan("http://robjhyndman.com/tsdldata/misc/kings.dat",skip=3) king.ts <- ts(kings) king.ts install.packages("TTR") library(TTR) par(mfrow=c(2 ,2)) plot(SMA(king.ts, n=2), main = "n=2") plot(SMA(king.ts, n=5), main = "n=5") plot(SMA(king.ts, n=10), main = "n=10") plot(SMA(king.ts, n=15), main = "n=15") par(mfrow=c(1,1)) smooth.king <- SMA(king.ts, n=5) smooth.king births <- scan("http://robjhyndman.com/tsdldata/data/nybirths.dat") births.ts <- ts(births, frequency = 12) births.comps <- decompose(births.ts) plot(births.comps) library(zoo) library(quantmod) data <- as.zoo(smooth.king) x1 <- Lag(data,1) new.data <- na.omit(data.frame(Lag.1 = x1, y = data)) head(new.data) model <- lm(y ~ Lag.1, new.data) model plot(model) plot(king.ts) # Introducing MXNet library library(mxnet) zero.matrix <- mx.nd.zeros(c(3,3)) zero.matrix ones.matrix <- mx.nd.ones(c(3,3)) ones.matrix...