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 [[alternative HTML version deleted]]