On 13-09-18 1:38 AM, meng wrote:
Oh,yes, I found out this according to your reply.Thanks.
As to time series analysis, in order to show the effect of smoothing or
filtering,the common command is:
plot(ts0);
lines(fitted(...))
But not "lines(fitted(...) ~ time(ts) )"
How to understand this then?
lines() and plot() are "generic functions". What it does depends on the
class of the first argument. To see what happens, you need to know the
class of ts0, or fitted(...), or fitted(...) ~ time(ts). I'd guess ts0
has some time series class, fitted(...) probably has class "numeric"
(though this would depend on the dots, since it is also generic), and
the formula has class "formula". "numeric" generally gets the default
method (plot.default, lines.default); "formula" usually has its own
methods (plot.formula, lines.formula), etc. Read up on this in An
Introduction to R for more details (sections 3.4 and 10.9).
Duncan Murdoch
Many thanks.
Best.
At 2013-09-18 08:49:51,"Duncan Murdoch" <murdoch.dun...@gmail.com> wrote:
On 13-09-17 6:36 PM, meng wrote:
Thanks for your reply.
Is "fitted(lm(...))" the same as "values" of lines(values)?
If yes,then why the range of lines(values) is different from
range(fitted(lm(...)))?
You are plotting against the wrong x axis, and you don't see all the values.
Duncan Murdoch
If no, what "values" refers to?
At 2013-09-17 20:56:04,"Duncan Murdoch" <murdoch.dun...@gmail.com> wrote:
On 13-09-17 8:06 AM, meng wrote:
Hi all:
I met a question about "lines".
attach(cars)
plot(dist ~ speed)
#add the regression line to the plot
lines(fitted(lm(dist~speed)) ~ speed)
plot(dist ~ speed)
#what kind of curve does the following command add to the plot?
lines(fitted(lm(dist~speed)))
My question is :
what kind of curve does the last command add to the plot?
Look at the class of fitted(lm(...)). It is "numeric". So what you're
seeing is the same as if you computed the fitted values, and then did
lines(values)
Since values is just a vector of numbers, that will plot them as y
values against x values 1:length(values). That's unlikely to be a
useful thing to do.
Duncan Murdoch
My guess:maybe the level of fitted values?
range(fitted(lm(dist~speed)))
[1] -1.84946 80.73112
But from the plot,I can see the range of the curve is about 10 to 40 more or
less,which is different from(-1.84946, 80.73112).So the curve must not be the
fitted values.What kind of curve does the last command add to the plot then?
Many thanks for your help
My best
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