search for: save2

...ing properly quoted somewhere down the line. The same issue can occur on the right hand side. "Save the model frame in case you need to refit something next month" is does not appear to be a safe approach to reproducable research. fit2 <- glm(y ~ sex + log(age), poisson, testdata) save2 <- fit2$model update(fit2, . ~ . - sex, data=save2) # fails glm(y ~ log(age), poisson, save2) # fails I can work around this in my anova, but I wanted to not rebuild the frame if it is already present. It looks like model.matrix plus attr(x, 'assign') time -- a bit harder to r...

...the number the way I'm thinking about the number? Cheers, Mark > dim(X) [1] 25 425 > > ReShapeX <- melt(X, id = c("Trade", "PosType", "EnDate", "EnTime", "ExDate", "ExTime", "PL_Pos", "Costs", "Save2")) > > dim(ReShapeX) [1] 10400 11 > > MyResults <- subset(ReShapeX, value > 0) > > dim(MyResults) [1] 1105 11 > > MyResults.GroupA <- subset(MyResults, PosType = 1) > > dim(MyResults.GroupA) [1] 1105 11 > > MyResults.GroupB <- subset(MyRes...

...me. On thing would the the ExNum value from the first occurrence at that crosspoint, or the PL_Pos value, etc. How might I write a fun.aggregate to to that? Thanks, Mark > dim(MyResults) [1] 1105 12 > head(MyResults, n=15) ExNum PosType EnDate EnTime ExDate ExTime PL_Pos Costs Save2 time value id 1.1 1 -1 1080103 800 1080103 1310 520 26 0 1 746.2 1 2.1 2 -1 1080104 755 1080104 1310 530 26 0 1 721.9 2 3.1 3 1 1080107 945 1080107 1310 -340 26 0 1 722.8 3 4.1 4 -1 1080108 820 1080108 1310...

...me. On thing would the the ExNum value from the first occurrence at that crosspoint, or the PL_Pos value, etc.    How might I write a fun.aggregate to to that? Thanks, Mark > dim(MyResults) [1] 1105   12 > head(MyResults, n=15)      ExNum PosType  EnDate EnTime  ExDate ExTime PL_Pos Costs Save2 time value id 1.1      1      -1 1080103    800 1080103   1310    520    26     0 1 746.2  1 2.1      2      -1 1080104    755 1080104   1310    530    26     0 1 721.9  2 3.1      3       1 1080107    945 1080107   1310   -340    26     0 1 722.8  3 4.1      4      -1 1080108    820 1080108   1310...