search for: ab4

...mes = vars, : Could not compute QR decomposition of Hessian. Optimization probably did not converge. ######### Model ######## mDPDF = data.frame(mj1,mj2,mj3,mj4,mj5,eL1,eL2,eL3,eL4,eL5,aC1,aC2,aC3,aC4,disR1,disR2,disR3,disR4,disR5, difR1,difR2,difR3,difR4,difR5,difR6,dC1,dC2,dC3,dC4,aB1,aB2,aB3,aB4,aB5,deh1,deh2,deh3,deh4) mydata.cov <- cov(mDPDF) model.mydata <- specify.model() MJ -> mj1, NA, 1 MJ -> mj2, lam2, NA MJ -> mj3, lam3, NA MJ -> mj4, lam4, NA MJ -> mj5, lam5, NA EL -> eL1, NA, 1 EL -> eL2, lam7, NA EL -> eL3, lam8, NA EL -> eL4, lam9, NA EL -> e...

I have two datasets: A with columns Open and Name (and many others, irrelevant to the merge) B with columns Time and Name (and many others, irrelevant to the merge) I want the dataset AB with all these columns Open from A - a difftime (time of day) Time from B - a difftime (time of day) Name (same in A & B) - a factor, does NOT index rows, i.e., there are _many_ rows in both A & B with

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