search for: 92l

Hi All, I have a scatter plot produced using ggplot2 and I want to add the regression line to this scatter plot. I suppose I can use geom_smooth() to do this, but for the sake of learning ( I am new both to R and ggplot2), I want to try and add it as a function (something that curve() does in the standard R plotting). I did some search and found that stat_function() can be used for this. But

...32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L, 112L, 113L, 114L, 115L, 116L, ...... ...... ..... V2 = structure(c(278L, 23L, 11L, 169L, 14L, 86L, 94L, 51L, 37L, 43L, 22L, 169L, 49L, 120L, 18L, 60L, 42L, 41L, 38L, 64L, 38L, 32L,...

...escing be allowed to coalesce a COPY that uses a subreg as a destination? I've got the following sequence of code (unfortunately for an out of tree target) that is moving 32 and 64 bit sub-registers around within a 128 bit register. By the time the register allocator runs the code looks like: 92L %reg16402:dsub0<def> = DEF64.. %reg16402<imp-def>, QPR:%reg16402.... 116L %reg16405:sub0<def> = COPY %reg16402:sub1, %reg16405<imp-def>; QPR:%reg16405,16402 124L %reg16413:sub0<def> = COPY %reg16405:sub0<kill>; QPR:%reg16413,16405 .... stuff .... 468L %reg16460...

...120, 1210110900, 1210110900, 1210118400, 1210126980, 1210134180, 1210142640, 1210156080, 1210164180, 1210176840, 1210183740), class = c("POSIXct", "POSIXt"), tzone = ""), Score = c(80L, 11L, 81L, 152L, 130L, 122L, 142L, 20L, 1L, 31L, 93L, 136L, 128L, 112L, 48L, 57L, 92L, 108L, 100L, 107L, 81L, 37L, 47L, 70L, 114L, 125L, 99L, 46L, 108L, 106L, 111L, 75L, 75L, 136L, 36L, 13L, 35L, 71L, 105L, 113L, 116L, 116L, 94L, 130L, 102L, 19L, 1L, 33L, 78L, 89L)), .Names = c("Date", "Score"), row.names = c(NA, 50L), class = "data.frame") I'm...

...edwoods > dput(flies) structure(list(long = c(40L, 37L, 44L, 47L, 47L, 47L, 68L, 47L, 54L, 61L, 71L, 75L, 89L, 58L, 59L, 62L, 79L, 96L, 58L, 62L, 70L, 72L, 74L, 96L, 75L, 46L, 42L, 65L, 46L, 58L, 42L, 48L, 58L, 50L, 80L, 63L, 65L, 70L, 70L, 72L, 97L, 46L, 56L, 70L, 70L, 72L, 76L, 90L, 76L, 92L, 21L, 40L, 44L, 54L, 36L, 40L, 56L, 60L, 48L, 53L, 60L, 60L, 65L, 68L, 60L, 81L, 81L, 48L, 48L, 56L, 68L, 75L, 81L, 48L, 68L, 35L, 37L, 49L, 46L, 63L, 39L, 46L, 56L, 63L, 65L, 56L, 65L, 70L, 63L, 65L, 70L, 77L, 81L, 86L, 70L, 70L, 77L, 77L, 81L, 77L, 16L, 19L, 19L, 32L, 33L, 33L, 30L, 42L, 42L,...

...107L, 15L, 25L, 39L, 1L, 71L, 95L, 19L, 56L, 62L, 76L, 85L, 99L, 111L, 42L, 4L, 52L, 61L, 67L, 91L, 13L, 24L, 36L, 38L, 7L, 81L, 82L, 57L, 64L, 100L, 113L, 21L, 33L, 44L, 78L, 54L, 73L, 83L, 108L, 16L, 28L, 2L, 58L, 65L, 86L, 101L, 32L, 43L, 77L, 93L, 104L, 10L, 48L, 53L, 97L, 110L, 18L, 27L, 75L, 92L, 103L, 31L, 9L, 47L, 70L, 72L, 106L, 14L, 26L, 40L, 79L, 98L, 112L, 68L, 88L, 105L, 20L, 11L, 49L, 63L, 5L, 80L, 50L, 59L, 89L, 114L, 22L, 34L, 45L), .Label = c("1/14/08 12:26", "1/15/08 15:25", "1/15/08 16:32", "1/16/08 11:36", "1/16/08 15:29", &qu...

Hello, It's an alternative to use SAS by function in R? I want to plot d histograms by plot.from example bellow: Thank you! plot d 1 1 16.3 2 1 25.0 3 1 57.8 4 1 17.0 5 2 10.8 13 2 96.4 17 3 76.0 18 3 32.0 19 3 11.0 20 3 11.0 24 3 106.0 25 3 12.5 21 4 19.3 22 4 12.0 26 4 15.0 27 5 99.3 32 7 11.0 36

...57.844799042 )), .Names = c("ptno", "age", "y"), row.names = c(1L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L), class = "data.frame") library(nlme) grpdat = groupedData(y ~ age | ptno, data = tmpdat, FUN = mean, labels = list(x...

...40, 1210613820, 1210618200, 1210633260, 1210640940, 1210650240, 1210663560, 1210677660, 1210686960, 1210695240, 1210705380), class = c("POSIXct", "POSIXt"), tzone = ""), Score = c(80L, 11L, 81L, 152L, 130L, 122L, 142L, 20L, 1L, 31L, 93L, 136L, 128L, 112L, 48L, 57L, 92L, 108L, 100L, 107L, 81L, 37L, 47L, 70L, 114L, 125L, 99L, 46L, 108L, 106L, 111L, 75L, 75L, 136L, 36L, 13L, 35L, 71L, 105L, 113L, 116L, 116L, 94L, 130L, 102L, 19L, 1L, 33L, 78L, 89L, 115L, 130L, 117L, 105L, 0L, 36L, 80L, 130L, 124L, 124L, 66L, 75L, 57L, 94L, 124L, 165L, 170L, 158L, 127L, 116L, 107...

...0L,? 24L, 347L, 419L, 135L, 202L, 294L, 173L, 121L, 358L, 51L, 231L,? 118L, 109L, 182L, 219L, 42L, 73L, 435L, 389L, 431L, 81L, 149L,? 388L, 415L, 256L, 312L, 446L, 45L, 162L, 485L, 154L, 55L, 153L,? 137L, 290L, 93L, 40L, 110L, 167L, 315L, 266L, 317L, 314L, 264L,? 277L, 488L, 28L, 354L, 303L, 490L, 192L, 432L, 228L, 222L, 418L,? 323L, 244L, 239L, 193L, 120L, 116L, 148L, 57L, 246L, 300L, 143L,? 208L, 400L, 78L, 273L, 411L, 401L, 476L, 262L, 159L, 195L, 102L,? 75L, 136L, 402L, 32L, 199L, 286L, 477L, 54L, 429L, 80L, 316L,? 30L, 333L, 387L, 452L, 324L, 456L, 39L, 138L, 113L, 448L, 377L,? 122L, 441L, 3...

...69L, 70L, 70L, 71L, 71L, 73L, 73L, 73L, 73L, 74L, 74L, 74L, 74L, 75L, 75L, 75L, 75L, 76L, 76L, 76L, 76L, 78L, 78L, 78L, 79L, 79L, 80L, 80L, 81L, 81L, 81L, 81L, 82L, 82L, 82L, 83L, 83L, 83L, 84L, 85L, 85L, 85L, 87L, 87L, 87L, 87L, 87L, 87L, 88L, 88L, 88L, 88L, 89L, 89L, 90L, 91L, 91L, 91L, 91L, 91L, 92L, 93L, 93L, 94L, 95L, 95L, 95L, 95L, 96L, 96L, 96L, 97L, 97L, 98L, 98L, 98L, 98L, 99L, 100L, 100L, 100L, 100L, 100L), d = c(15, 27.5, 10.5, 12.25, 14, 32.5, 80, 49.5, 15.25, 13.5, 12.25, 12, 72.5, 68.5, 12, 9.25, 12.75, 13.5, 28, 38, 10.25, 62.5, 73.5, 61.5, 54.5, 40, 24.25, 43, 13, 20.75, 23.25, 25...

...5L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 1...

...-116L, -122L, -112L, -125L, -109L, -114L, -118L, -102L, -109L, -101L, -101L, -74L, -78L, -63L, -67L, -75L, -65L, -60L, -62L, -67L, -59L, -62L, -68L, -61L, -58L, -69L, -57L, -59L, -67L, -73L, -81L, -90L, -87L, -82L, -80L, -80L, -81L, -83L, -90L, -89L, -107L, -122L, -128L, -113L, -124L, -93L, -89L, -92L, -85L, -79L, -84L, -83L, -148L, -142L, -127L, -130L, -123L, -131L, -85L, -87L, -90L, -81L, -65L, -81L, -119L, -121L, -94L, -90L, -117L, -95L, -69L, -122L, -103L, -85L, -106L)), .Names = c("mine", "dCu65", "dD"), class = "data.frame", row.names = c(NA, -130L))

I have been working with the pls procedure and have problems getting the procedure to work with matrix or frame data. I suspect the problem lies in my understanding of frames, but can't find anything in the documentation that will help. Here is what I have done: I read in an 10000 x 8 table of data, and assign the first four columns to matrix A and the second four to matrix B pls <-

...onductivity", "LithClass"), row.names = c(1L, 2L, 4L, 5L, 6L, 7L, 8L, 12L, 14L, 16L, 17L, 20L, 21L, 23L, 24L, 26L, 27L, 28L, 30L, 31L, 35L, 36L, 37L, 38L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 55L, 56L, 58L, 59L, 61L, 62L, 65L, 66L, 67L, 69L, 71L, 72L, 76L, 78L, 79L, 80L, 88L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 112L), class = "data.frame") The data (in the "structure") is removed, but the labels for all LithClass remain. If I then produce a boxplot or some other graphic where LithClass is involve...

Folks, I have a data frame with columns 200401, 200402, ..., 201207, 201208. These represent years/months. What would be the best way to sum these columns by year? What about by quarter? Thanks for your time, KW -- [[alternative HTML version deleted]]

...48L, 59L, 62L, 63L, 64L, 65L, 66L, 67L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 60L, 61L, 68L, 79L, 90L, 93L, 94L, 95L, 96L, 97L, 98L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 77L, 78L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 91L, 92L, 99L, 110L, 121L, 123L, 124L, 125L, 126L, 127L, 128L, 100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 111L, 112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 122L, 2L, 13L, 24L, 27L, 28L, 29L, 30L, 31L, 32L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 14L, 15L, 16L, 17L, 18L, 19L, 20...

...42L, 240L, 238L, 239L, 235L, 236L, 237L, 234L, 232L, 233L, 231L, 229L, 230L, 226L, 228L, 227L, 223L, 225L, 224L, 220L, 221L, 222L, 217L, 219L, 218L, 214L, 216L, 215L, 211L, 212L, 213L, 210L, 208L, 209L, 207L, 205L, 206L, 202L, 204L, 203L, 201L, 199L, 200L, 196L, 197L, 198L, 195L, 193L, 194L, 190L, 192L, 191L, 189L, 187L, 188L, 184L, 185L, 186L, 183L, 181L, 182L, 178L, 180L, 179L, 175L, 177L, 176L, 172L, 174L, 173L, 171L, 169L, 170L, 166L, 168L, 167L, 163L, 165L, 164L, 162L, 160L, 161L, 159L, 157L, 158L, 156L, 154L, 155L, 153L, 151L, 152L, 148L, 150L, 149L, 147L, 145L, 146L, 142L, 143L, 144L, 139L...

...L, 63L, 62L, 43L, 6L, 44L, 87L, 5L, 31L, 61L, 79L, 55L, 36L, 67L, 2L, 32L, 108L, 47L, 66L, 86L, 88L, 122L, 11L, 16L, 94L, 95L, 115L, 123L, 24L, 80L, 78L, 111L, 103L, 3L, 22L, 23L, 10L, 107L, 97L, 75L, 96L, 106L, 102L, 118L, 7L, 110L, 30L, 59L, 76L, 114L, 74L, 104L, 1L, 64L, 73L, 54L, 58L, 19L, 69L, 92L, 14L, 119L, 18L, 127L, 41L, 15L, 8L, 49L, 91L, 65L, 120L, 113L, 93L, 17L, 126L, 29L, 105L, 90L, 77L, 81L, 45L, 38L, 85L, 39L, 53L, 9L, 121L, 125L, 109L, 101L, 48L, 52L, 84L, 21L, 60L, 72L, 56L, 124L, 57L, 12L, 112L, 13L, 4L, 26L, 89L, 116L, 27L, 128L, 20L, 117L, 40L, 33L, 28L, 37L, 25L), class = &q...

...= c(135L, 118L, 121L, 64L, 53L, 49L, 178L, 123L, 128L, 127L, 62L, 129L, 126L, 99L, 183L, 45L, 57L, 45L, 72L, 30L, 71L, 123L, 89L, 102L, 60L, 44L, 59L, 124L, 145L, 126L, 103L, 67L, 97L, 66L, 76L, 108L, 36L, 48L, 41L, 69L, 47L, 57L, 167L, 136L, 176L, 85L, 36L, 82L, 222L, 149L, 171L, 145L, 122L, 192L, 136L, 164L, 154L, 46L, 57L, 57L, 70L, 55L, 102L, 111L, 152L, 204L, 41L, 46L, 103L, 156L, 148L, 155L, 103L, 124L, 176L, 111L, 142L, 187L, 43L, 52L, 75L, 64L, 91L, 78L, 196L, 314L, 265L, 44L, 39L, 98L, 197L, 273L, 274L, 89L, 91L, 74L, 91L, 112L, 98L, 140L, 90L, 121L, 120L, 161L, 83L, 230L, 266L,...