R help - Oct 2023 - Plot for 10 years extrapolation

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")
########################################################

from ?predict.lm:

"predict.lm produces a vector of predictions or a matrix of
predictions and bounds with column names fit, lwr, and upr if interval
is set. "

ergo:
predict(model, dfuture, interval = "prediction")[,"fit"]  ##
or [,1]
as it's the first column in the returned matrix

is your vector of predicted values that you can plot against
dfuture$date however you would like, e.g. with different colors,
symbols, or whatever. Exactly how you do this depends on what graphics
package you are using. The example in ?predict.lm shows you how to do
it with R's base graphics and overlaying prediction and confidence
intervals.

Cheers,
Bert

On Thu, Oct 26, 2023 at 11:27?AM varin sacha via R-help
<r-help at r-project.org> wrote:
>
> 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")
> ########################################################
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

?s 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")
> ########################################################
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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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