Felhasznált adatbázisok:

 Adatok beolvasása:

# Parent-Duchatelet's time-series data on the number of prostitutes in Paris
read.csv('http://ppke.snowl.net/files/2012/12/Paris.csv')

# Daily maximum temperature in NY (1960-1965)
read.csv('http://ppke.snowl.net/files/2012/12/NY.csv')

Elemzés:

df <- read.csv('http://ppke.snowl.net/files/2012/12/Paris.csv')

df$ho <- 1:12
df$ev <- rep(1812:1854, each = 12)

fit <- lm(df$x ~ poly(df$ho, 2) + df$ev)
fit
plot(df$x, type = "l")
lines(predict(fit), col="red")

fit <- lm(df$x ~ poly(df$ev, 6))
plot(df$x, type = "l")
lines(predict(fit), col="red")

fit <- lm(df$x ~ poly(df$ev, 15))
plot(df$x, type = "l")
lines(predict(fit), col="red")

t <- ts(df$x, start = c(1812, 1), freq = 12)

decompose(t)
plot(decompose(t))

###########################################

df <- read.csv('http://ppke.snowl.net/files/2012/12/NY.csv')

fit <- lm(df$temp ~ df$month)
plot(df$temp, type = "l")
lines(predict(fit), col="red")

fit <- lm(df$temp ~ poly(df$month, 2))
plot(df$temp, type = "l")
lines(predict(fit), col="red")

t <- ts(df$temp, start =  c(1960, 1), freq = 365)
decompose(t)
plot(decompose(t))