Dear Rui,
I really thank you a lot for your precious R help. It is exactly what I was
trying to do! Once more, many thanks!
Best,
Sacha
Le vendredi 27 octobre 2023 à 09:36:18 UTC+2, Rui Barradas
<ruipbarra...@sapo.pt> a écrit :
Às 19:23 de 26/10/2023, varin sacha via R-help escreveu:
> Dear R-Experts,
>
> Here below my R code working but I don't know how to complete/finish my R
> code to get the final plot with the extrapolation for the10 more years.
>
> Indeed, I try to extrapolate my data with a linear fit over the next 10
> years. So I create a date sequence for the next 10 years and store as a
> dataframe to make the prediction possible.
> Now, I am trying to get the plot with the actual data (from year 2004 to
> 2018) and with the 10 more years extrapolation.
>
> Thanks for your help.
>
> ####################################################
> date <-as.Date(c("2018-12-31", "2017-12-31", "2016-12-31", "2015-12-31",
> "2014-12-31", "2013-12-31", "2012-12-31", "2011-12-31", "2010-12-31",
> "2009-12-31", "2008-12-31", "2007-12-31", "2006-12-31", "2005-12-31",
> "2004-12-31"))
>
> value <-c(15348, 13136, 11733, 10737, 15674, 11098, 13721, 13209, 11099,
> 10087, 14987, 11098, 13421, 9023, 12098)
>
> model <- lm(value~date)
>
> plot(value~date ,col="grey",pch=20,cex=1.5,main="Plot")
> abline(model,col="darkorange",lwd=2)
>
> dfuture <- data.frame(date=seq(as.Date("2019-12-31"), by="1 year",
> length.out=10))
>
> predict(model,dfuture,interval="prediction")
> ########################################################
>
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Hello,
Here is a way with base R graphics. Explained in the code comments.
####################################################
date <-as.Date(c("2018-12-31", "2017-12-31", "2016-12-31",
"2015-12-31", "2014-12-31", "2013-12-31",
"2012-12-31", "2011-12-31", "2010-12-31",
"2009-12-31", "2008-12-31", "2007-12-31",
"2006-12-31", "2005-12-31", "2004-12-31"))
value <-c(15348, 13136, 11733, 10737, 15674, 11098, 13721, 13209,
11099, 10087, 14987, 11098, 13421, 9023, 12098)
model <- lm(value ~ date)
dfuture <- data.frame(date = seq(as.Date("2019-12-31"), by="1 year",
length.out=10))
########################################################
predfuture <- predict(model, dfuture, interval="prediction")
dfuture <- cbind(dfuture, predfuture)
# start the plot with the required x and y limits
xlim <- range(c(date, dfuture$date))
ylim <- range(c(value, dfuture$fit))
plot(value ~ date, col="grey", pch=20, cex=1.5, main="Plot"
, xlim = xlim, ylim = ylim)
# abline extends the fitted line past the x value (date)
# limit making the next ten years line ugly and not even
# completely overplotting the abline drawn line
abline(model, col="darkorange", lwd=2)
lines(fit ~ date, dfuture
# , lty = "dashed"
, lwd=2
, col = "black")
# if lines() is used for both the interpolated and extrapolated
# values you will have a gap between both fitted and predicted lines
# but it is closer to what you want
# get the fitted values first (interpolated values)
ypred <- predict(model)
plot(value ~ date, col="grey", pch=20, cex=1.5, main="Plot"
, xlim = xlim, ylim = ylim)
# plot the interpolated values
lines(ypred ~ date, col="darkorange", lwd = 2)
# and now the extrapolated values
# I use normal orange to make the difference more obvious
lines(fit ~ date, dfuture, lty = "dashed", lwd=2, col = "orange")
Hope this helps,
Rui Barradas
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