lm and time series.
On Fri, 5 Sep 2008, rkevinburton at charter.net wrote:
That is the thing. As a new comer to 'R' I don't understand how to write a formula when all I have is a time series. I don't know how to express the independent and dependent variables in a formula when the object is a time series. So please just solve this simple example and I will extrapolate from there. Say the units of the time series is days and the value at each point is the response. If I wanted to fit a straiight line through the following time series: y <- 4:7 t <- ts(y) So this is saying to me something like 4 units were sold on the first day, 5 on the second, 6 on the third, and 7 on the fourth. So given the time series t I want to find the slope and inercept: y = m*x + b with x in days and the respoinse would be the number of units sold. I need to find 'm' and 'b'. If all I have is t (the time series above) then what would be the formula, and for that matter the arguments to lm to give the desired result? fit <- lm(???)
y <- ts(4:7) lm(y ~ time(y)) And as previously pointed out to you: To preserve the time series properties, look at ?lm, the "dynlm" and "dyn" packages. Z
Thank you. Kevin ---- stephen sefick <ssefick at gmail.com> wrote:
So you want time as the independent variable? Let's say that the units of y in your first example were seconds- couldn't you just use a regular lm and say that the units were seconds, minutes, or what ever? I am probably out of my league here, but I am just not understanding what it is that you want. a time series is just a series of data points indexed by time. Arima maybe, or some other cool times series modeling approach- wavelet, spectral density- for frequency domain type things... What are you trying to accomplish? On Fri, Sep 5, 2008 at 5:47 PM, <rkevinburton at charter.net> wrote:
I want to fit a function to time series. If I had: x <- 1:4 y <- 1:4 lm(y~x) This would fit a simple line to the four points. But if it is represented as a time series x <- 1:4 t <- ts(x) lm(????) So I have a time series in the object t. How do I write a formula for lm? What do I put in the formula for x and y when I only have t (the time series). Kevin ---- stephen sefick <ssefick at gmail.com> wrote:
what do you want to do? On Fri, Sep 5, 2008 at 3:22 PM, <rkevinburton at charter.net> wrote:
I am sorry but I looked at ?lm and could not see any guidance on writting a formula. If I have two arrays or a data set then I know how to do that (y ~ x) but for a time series I am not sure how to write y or x. Thank you. Kevin ---- Gabor Grothendieck <ggrothendieck at gmail.com> wrote:
The Time Series section in ?lm should be self explanatory. If you are using diff's and lag's then look at the dyn package. On Fri, Sep 5, 2008 at 12:25 PM, <rkevinburton at charter.net> wrote:
I did a ?lm and it said basically to be careful when using lm and a time series. But my question is probably more to do with my inexperience that anything. If I have a time series object 'ti' how do I write the formula? The response is the value at any particular time and the time is basically the index of the time series. But I don't know how to put that into a formula. Thank you. Kevin
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--
Stephen Sefick
Research Scientist
Southeastern Natural Sciences Academy
Let's not spend our time and resources thinking about things that are
so little or so large that all they really do for us is puff us up and
make us feel like gods. We are mammals, and have not exhausted the
annoying little problems of being mammals.
-K. Mullis
-- Stephen Sefick Research Scientist Southeastern Natural Sciences Academy Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problems of being mammals. -K. Mullis
______________________________________________ R-help at r-project.org mailing list 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.