Hello all,
I'm using R version 2.0.1. I have been having trouble with my linear
modeling. I have a table that looks something like this:
T RSS DS S LS PF COLS PS
R RTT Actual Max COMM
char 50000 MSS 2 1250000 1 1
4096 450 0.001 64.30 0.13 64.17
char 50000 MSS 50 1250000 1 25
4096 450 0.001 74.97 0.14 74.83
char 50000 MSS 200 1250000 1 100
4096 450 0.001 111.12 0.13 110.99
char 50000 MSS 3 1250000 1 1
4096 450 0.001 64.31 0.14 64.17
char 50000 MSS 75 1250000 1 25
4096 450 0.001 75.99 0.14 75.85
char 50000 MSS 300 1250000 1 100
4096 450 0.001 116.62 0.14 116.48
that I was modeling using the R command
model.f <- lm(comm ~ I(rtt * ceiling(rss/pf)) + I((s * rss) / ls) +
ds*(I(((s+s^2)*rss)/r) + I(((s+s^2)*rss)/(r*ps))))
R gives me a table like this for coefficients
I(rtt * ceiling(rss/pf)) I((s *
rss)/ls)
8.174598e-01
1.353734e+00
dsASA
dsDB2
3.101663e+00
2.587372e+00
dsMSS
dsOracle
1.575822e+01
9.092041e+00
I(((s + s^2) * rss)/r) I(((s + s^2) * rss)/(r *
ps))
2.151170e-07
3.087502e-05
dsDB2:I(((s + s^2) * rss)/r) dsMSS:I(((s + s^2) *
rss)/r)
-6.972409e-08
1.812149e-07
dsOracle:I(((s + s^2) * rss)/r) dsDB2:I(((s + s^2) * rss)/(r *
ps))
1.251699e-08
6.687324e-05
dsMSS:I(((s + s^2) * rss)/(r * ps)) dsOracle:I(((s + s^2) * rss)/(r *
ps))
4.731049e-05
-9.243794e-05
What I want at the end of the day is a formula that says "given this set of
parameters, here is the predicted value". When I plug the above
coefficients
into Excel, I get a value that is WAY off the fitted value that R gives me.
My questions are:
1) How do I use these coefficients in a formula?
2) How can I construct a formula from these coefficients that I can publish
in my thesis?
Thanks for your help!
ty
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