search for: 107l

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

...210618200, 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, 107L, 118L, 150L, 96...

..., -0.8, 5.8, 0.6, 1, 0.9, 4.4, 2.3, -0.1), dD = c(-66L, -81L, -81L, -71L, -68L, -79L, -73L, -77L, -74L, -71L, -73L, -80L, -76L, -80L, -74L, -77L, -74L, -77L, -74L, -82L, -79L, -72L, -74L, -71L, -76L, -72L, -76L, -73L, -75L, -78L, -81L, -77L, -77L, -73L, -79L, -104L, -98L, -98L, -109L, -106L, -99L, -107L, -100L, -98L, -95L, -95L, -95L, -97L, -98L, -121L, -119L, -118L, -121L, -121L, -106L, -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...

...L, 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, 140L, 146L, 106L, 26L, 46L, 65L, 17L, 106L, 20L, 33L, 68L, 62L, 111L, 10L, 149...

...210110900, 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 trying to round th...

...190L, 198L, 61L, 61L, 119L, 148L, 202L, 202L, 61L, 61L, 119L, 148L, 185L, 202L, 215L )), .Names = c("TSS", "GPP", "RiverMile"), class = "data.frame", row.names = c(12L, 13L, 14L, 19L, 25L, 26L, 28L, 34L, 35L, 36L, 37L, 42L, 44L, 58L, 75L, 85L, 88L, 91L, 97L, 107L, 142L, 144L, 155L, 166L, 169L, 185L, 186L, 201L, 202L, 207L, 219L, 221L, 222L, 224L, 226L, 230L, 231L, 250L, 251L, 258L, 283L, 287L, 288L, 303L, 304L, 306L, 311L, 313L))) library(lattice) library(ggplot2) z <- nls(GPP~(a/(TSS+b)), start=c(a=0.01, b=0.01), data=r) f <- seq(-1, 29, length=100)...

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

...", "E", "F", "G", "H", "I", "J", "K"), class = "factor"), Yes = c(18L, 2L, 1L, 2L, 44L, 27L, 2L, 15L, 13L, 3L, 34L), No = c(171L, 11L, 5L, 8L, 146L, 80L, 5L, 30L, 22L, 5L, 42L), Num = c(189L, 13L, 6L, 10L, 190L, 107L, 7L, 45L, 35L, 8L, 76L)), .Names = c("Case", "Yes", "No", "Num"), class = "data.frame", row.names = c(NA, -11L)) Thanks in advance Sam

what am I doing wrong? chron(as.character(f), format=c(dates="%m/%d/%y", times="%h:%m")) f <- structure(c(51L, 60L, 66L, 87L, 90L, 115L, 23L, 35L, 37L, 6L, 12L, 55L, 84L, 96L, 109L, 17L, 29L, 41L, 3L, 74L, 94L, 102L, 30L, 8L, 46L, 69L, 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,...

....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="Age", y="Y")) fit.lme = lme(grpdat) plot(augPred( fit.l...

...c(428L, 359L, 353L, 498L, 169L, 46L, 29L, 444L, 194L,? 439L, 284L, 79L, 226L, 105L, 106L, 326L, 234L, 196L, 417L, 190L,? 480L, 275L, 478L, 341L, 197L, 395L, 85L, 295L, 70L, 18L, 471L,? 218L, 19L, 43L, 280L, 427L, 229L, 5L, 205L, 494L, 393L, 307L,? 465L, 383L, 265L, 103L, 348L, 166L, 58L, 320L, 14L, 107L, 440L,? 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, 490...

I'm trying to read a binary file created by a fortran code using readBin and readChar. Everything reads fine (integers and strings) except for double precision numbers, they are read as huge or very small number (1E-250,...). I tried various endianness, swap, But nothing has worked so far. I also tried on R 64 bit for linux and windows (R 2.14) and R 2.11 on windows XP 32 bit. Any help would

...L, 933L, 0L, 14L, 388L, 1180L, 1709L), V4 = c(0L, 0L, 0L, 0L, 0L, 0L, 3L, 12L, 0L, 0L, 2L, 1L, 36L, 45L, 208L, 7L, 221L, 213L, 371L, 1440L, 26L, 211L, 389L, 1382L, 1614L), V5 = c(96L, 7L, 0L, 0L, 0L, 10L, 17L, 0L, 5L, 0L, 0L, 11L, 151L, 127L, 160L, 27L, 388L, 439L, 1117L, 1571L, 81L, 598L, 1107L, 1402L, 891L), V6 = c(16L, 30L, 13L, 0L, 0L, 10L, 195L, 60L, 29L, 29L, 1L, 107L, 698L, 596L, 655L, 227L, 287L, 677L, 1477L, 1336L, 425L, 873L, 961L, 1360L, 1175L), V7 = c(249L, 101L, 69L, 0L, 18L, 186L, 331L, 291L, 259L, 248L, 336L, 404L, 642L, 632L, 775L, 455L, 801L, 697L, 1063L, 978L, 6...

...160, 114, 80, 24, 132, 165, 137, 166, 103, 143, 47, 34, 121, 79, 9, 121, 85, 130, 96, 72, 40, 9, 160, 47, 6, 166, 166, 130, 88, 39)), .Names = c("id", "ftime", "rcat", "tdiff"), row.names = c(11L, 4L, 13L, 25L, 39L, 41L, 35L, 44L, 54L, 57L, 96L, 98L, 88L, 107L, 80L, 77L, 118L, 136L, 124L, 146L, 150L, 157L, 153L, 169L, 196L, 210L, 214L, 225L, 230L, 221L, 222L, 258L, 266L, 281L, 311L, 324L, 333L, 334L, 358L, 372L, 400L, 419L, 423L, 434L, 439L, 437L, 443L, 479L, 465L, 496L, 517L, 516L, 519L, 525L, 539L, 598L, 606L, 634L, 658L, 649L, 637L, 655L, 640L, 64...

...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 involved, blank plots are produced for the deleted LithClass labels, which is not wh...

...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, 20L, 21L, 22L, 23L, 25L, 26L, 33L, 34L, 35L, 36L), .Label = c("", "10/1/2008", &quo...

...156L, 154L, 155L, 153L, 151L, 152L, 148L, 150L, 149L, 147L, 145L, 146L, 142L, 143L, 144L, 139L, 140L, 141L, 138L, 137L, 136L, 135L, 133L, 134L, 132L, 130L, 131L, 127L, 129L, 128L, 126L, 124L, 125L, 121L, 122L, 123L, 120L, 118L, 119L, 117L, 115L, 116L, 112L, 114L, 113L, 109L, 110L, 111L, 106L, 108L, 107L, 105L, 103L, 104L, 102L, 100L, 101L, 99L, 97L, 98L, 94L, 96L, 95L, 93L, 91L, 92L, 90L, 88L, 89L, 85L, 86L, 87L, 84L, 82L, 83L, 81L, 79L, 80L, 76L, 77L, 78L, 75L, 73L, 74L, 72L, 70L, 71L, 69L, 67L, 68L, 66L, 64L, 65L, 61L, 62L, 63L, 60L, 58L, 59L, 55L, 56L, 57L, 54L, 52L, 53L, 51L, 49L, 50L, 46L, 48...

...ered", "pchloc"), row.names = c(98L, 99L, 71L, 100L, 70L, 51L, 68L, 83L, 34L, 35L, 82L, 50L, 42L, 46L, 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, 7...

...190L, 198L, 61L, 61L, 119L, 148L, 202L, 202L, 61L, 61L, 119L, 148L, 185L, 202L, 215L )), .Names = c("TSS", "GPP", "RiverMile"), class = "data.frame", row.names = c(12L, 13L, 14L, 19L, 25L, 26L, 28L, 34L, 35L, 36L, 37L, 42L, 44L, 58L, 75L, 85L, 88L, 91L, 97L, 107L, 142L, 144L, 155L, 166L, 169L, 185L, 186L, 201L, 202L, 207L, 219L, 221L, 222L, 224L, 226L, 230L, 231L, 250L, 251L, 258L, 283L, 287L, 288L, 303L, 304L, 306L, 311L, 313L))) library(lattice) z <- nls(GPP~(a/(TSS+b)), start=c(a=0.01, b=0.01), data=r) f <- seq(-1, 29, length=100) y <- coef(z)[...

Dear R-helpers, I have a dataset named "qu", organized as follows: Sample Run Replicate Value 1 1 1 25 1 1 2 40 1 1 3 33 1 1 4 29 1 2 1 37 1 2 2 44 1 2 3 45 1 3 1 25 1 3 2 40 1 4 1 33 1 4 2 29 1 4 3 25 2 ... Basically, a sample was run on an assay multiple times within a single day. Each of these results is "Replicate". Then run was repeated several times in