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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