# NOT RUN {
library(clr)
data(gb_load)
clr_load <- clrdata(x = gb_load$ENGLAND_WALES_DEMAND,
order_by = gb_load$TIMESTAMP,
support_grid = 1:48)
head(clr_load)
dim(clr_load)
summary(clr_load)
matplot(t(clr_load), ylab = 'Daily loads', type = 'l')
lines(colMeans(clr_load, na.rm = TRUE),
col = 'black', lwd = 2)
clr_weather <- clrdata(x = gb_load$TEMPERATURE,
order_by = gb_load$TIMESTAMP,
support_grid = 1:48)
summary(clr_weather)
plot(1:48,
colMeans(clr_weather, na.rm = TRUE),
xlab = 'Instant', ylab = 'Mean of temperatures',
type = 'l', col = 'cornflowerblue')
# }
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