Hi: I need some help with the legend. I got 14 samples(Muestreo) and I am trying to plot a smooth line for each sample. I am able to accomplish that but the problem is that the legend only displays every other sample. How can I force the legend to show all of my Muestreos? Thanks in advance.
fish_ByMuestreo <- structure(list(data = structure(list(SampleDate = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 16L, 16L, 16L, 7L, 7L, 7L, 7L, 10L, 10L, 10L, 13L, 13L, 13L, 13L, 13L, 27L, 27L, 27L, 27L, 27L, 17L, 17L, 17L, 17L, 20L, 20L, 20L, 20L, 24L, 24L, 24L, 24L, 24L, 30L, 30L, 30L, 30L, 42L, 42L, 42L, 42L, 42L, 33L, 33L, 33L, 33L, 36L, 36L, 36L, 36L, 36L, 39L, 39L, 39L, 39L, 39L, 39L, 14L, 14L, 14L, 14L, 14L, 14L, 5L, 5L, 5L, 8L, 8L, 8L, 11L, 11L, 11L, 11L, 15L, 15L, 15L, 28L, 28L, 28L, 28L, 28L, 18L, 18L, 18L, 18L, 18L, 22L, 22L, 22L, 22L, 25L, 25L, 25L, 25L, 40L, 40L, 40L, 40L, 40L, 31L, 31L, 31L, 31L, 37L, 37L, 37L, 37L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 16L, 16L, 16L, 7L, 7L, 7L, 7L, 10L, 10L, 10L, 13L, 13L, 13L, 13L, 13L, 27L, 27L, 27L, 27L, 27L, 17L, 17L, 17L, 17L, 20L, 20L, 20L, 20L, 24L, 24L, 24L, 24L, 24L, 30L, 30L, 30L, 30L, 42L, 42L, 42L, 42L, 42L, 33L, 33L, 33L, 33L, 36L, 36L, 36L, 36L, 36L, 14L, 14L, 14L, 14L, 14L, 14L, 5L, 5L, 5L, 8L, 8L, 8L, 11L, 11L, 11L, 11L, 15L, 15L, 15L, 28L, 28L, 28L, 28L, 28L, 18L, 18L, 18L, 18L, 18L, 22L, 22L, 22L, 22L, 25L, 25L, 25L, 25L, 40L, 40L, 40L, 40L, 40L, 31L, 31L, 31L, 31L, 34L, 34L, 34L, 34L, 34L, 37L, 37L, 37L, 37L, 1L, 1L, 1L, 1L, 1L, 6L, 6L, 6L, 6L, 6L, 6L, 9L, 9L, 9L, 12L, 12L, 12L, 21L, 21L, 21L, 21L, 29L, 29L, 29L, 19L, 19L, 19L, 19L, 19L, 23L, 23L, 23L, 23L, 23L, 26L, 26L, 26L, 26L, 41L, 41L, 41L, 41L, 32L, 32L, 32L, 32L, 32L, 35L, 35L, 35L, 35L, 38L, 38L, 38L, 38L, 38L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 16L, 16L, 16L, 7L, 7L, 7L, 7L, 10L, 10L, 10L, 13L, 13L, 13L, 13L, 13L, 27L, 27L, 27L, 27L, 27L, 17L, 17L, 17L, 17L, 20L, 20L, 20L, 20L, 24L, 24L, 24L, 24L, 24L, 30L, 30L, 30L, 30L, 42L, 42L, 42L, 42L, 42L, 33L, 33L, 33L, 33L, 36L, 36L, 36L, 36L, 36L, 39L, 39L, 39L, 39L, 39L, 39L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 16L, 16L, 16L, 7L, 7L, 7L, 7L, 10L, 10L, 10L, 13L, 13L, 13L, 13L, 13L, 27L, 27L, 27L, 27L, 27L, 17L, 17L, 17L, 17L, 20L, 20L, 20L, 20L, 24L, 24L, 24L, 24L, 24L, 30L, 30L, 30L, 30L, 42L, 42L, 42L, 42L, 42L, 33L, 33L, 33L, 33L, 36L, 36L, 36L, 36L, 36L, 39L, 39L, 39L, 39L, 39L, 39L), .Label = c("10/2/2002", "10/4/2002", "6/23/2002", "6/30/2002", "7/10/2002", "7/12/2002", "7/14/2002", "7/17/2002", "7/19/2002", "7/21/2002", "7/24/2002", "7/26/2002", "7/28/2002", "7/3/2002", "7/31/2002", "7/7/2002", "8/11/2002", "8/14/2002", "8/16/2002", "8/18/2002", "8/2/2002", "8/21/2002", "8/23/2002", "8/25/2002", "8/28/2002", "8/30/2002", "8/4/2002", "8/7/2002", "8/9/2002", "9/1/2002", "9/11/2002", "9/13/2002", "9/15/2002", "9/18/2002", "9/20/2002", "9/22/2002", "9/25/2002", "9/27/2002", "9/29/2002", "9/4/2002", "9/6/2002", "9/8/2002"), class = "factor"), PondName = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L), .Label = c("Pond01", "Pond02", "Pond03", "Pond04", "Pond05", "Pond06", "Pond07"), class = "factor"), Muestreo = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 15L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 15L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 15L), BodyWeight.g. = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 12, 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, 17, 16, 17, 15.5, 18, 18, 18, 17, 18, 19, 21, 21, 21, 25, 22, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 12, 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 17, 15.5, 18, 18, 18, 17, 18, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 11, 10, 12, 10.5, 12, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, 17, 16, 17, 15.5, 18, 18, 18, 17, 18, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 12, 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, 17, 16, 17, 15.5, 18, 18, 18, 17, 18, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 12, 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, 17, 16, 17, 15.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 12, 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, 17, 16, 17, 15.5, 18, 18, 18, 17, 18, 19, 21, 21, 21, 25, 22, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 12, 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, 17, 16, 17, 15.5, 18, 18, 18, 17, 18, 19, 21, 21, 21, 25, 22), Length.mm. = c(2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, 12L, 11L, 12L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 16L, 17L, 18L, 19L, 17L, 18L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, 12L, 11L, 12L, 12L, 13L, 14L, 12L, 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 11L, 12L, 11L, 12L, 10L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, 12L, 11L, 12L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, 12L, 11L, 12L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, 14L, 15L, 16L, 16L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, 12L, 11L, 12L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 16L, 17L, 18L, 19L, 17L, 18L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, 12L, 11L, 12L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 16L, 17L, 18L, 19L, 17L, 18L)), .Names = c("SampleDate", "PondName", "Muestreo", "BodyWeight.g.", "Length.mm."), class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", "69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79", "80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90", "91", "92", "93", "94", "95", "96", "97", "98", "99", "100", "101", "102", "103", "104", "105", "106", "107", "108", "109", "110", "111", "112", "113", "114", "115", "116", "117", "118", "119", "120", "121", "122", "123", "124", "125", "126", "127", "128", "129", "130", "131", "132", "133", "134", "135", "136", "137", "138", "139", "140", "141", "142", "143", "144", "145", "146", "147", "148", "149", "150", "151", "152", "153", "154", "155", "156", "157", "158", "159", "160", "161", "162", "163", "164", "165", "166", "167", "168", "169", "170", "171", "172", "173", "174", "175", "176", "177", "178", "179", "180", "181", "182", "183", "184", "185", "186", "187", "188", "189", "190", "191", "192", "193", "194", "195", "196", "197", "198", "199", "200", "201", "202", "203", "204", "205", "206", "207", "208", "209", "210", "211", "212", "213", "214", "215", "216", "217", "218", "219", "220", "221", "222", "223", "224", "225", "226", "227", "228", "229", "230", "231", "232", "233", "234", "235", "236", "237", "238", "239", "240", "241", "242", "243", "244", "245", "246", "247", "248", "249", "250", "251", "252", "253", "254", "255", "256", "257", "258", "259", "260", "261", "262", "263", "264", "265", "266", "267", "268", "269", "270", "271", "272", "273", "274", "275", "276", "277", "278", "279", "280", "281", "282", "283", "284", "285", "286", "287", "288", "289", "290", "291", "292", "293", "294", "295", "296", "297", "298", "299", "300", "301", "302", "303", "304", "305", "306", "307", "308", "309", "310", "311", "312", "313", "314", "315", "316", "317", "318", "319", "320", "321", "322", "323", "324", "325", "326", "327", "328", "329", "330", "331", "332", "333", "334", "335", "336", "337", "338", "339", "340", "341", "342", "343", "344", "345", "346", "347", "348", "349", "350", "351", "352", "353", "354", "355", "356", "357", "358", "359", "360", "361", "362", "363", "364", "365", "366", "367", "368", "369", "370", "371", "372", "373", "374", "375", "376", "377", "378", "379", "380", "381", "382", "383", "384", "385", "386", "387", "388", "389", "390", "391", "392", "393", "394", "395", "396", "397", "398", "399", "400", "401", "402", "403", "404", "405", "406", "407", "408", "409", "410", "411", "412", "413", "414", "415", "416", "417", "418", "419", "420", "421", "422", "423", "424", "425", "426", "427", "428")) library(ggplot2) fishplot <- qplot(PondName,BodyWeight.g.,data=fish_ByMuestreo,colour=Muestreo,position="jitter") + stat_summary(aes(group=Muestreo),fun.data="mean_cl_normal",colour="green",geom="smooth",fill=NA) + opts(title="Average weight(grs) by Pond") print(fishplot) Felipe D. Carrillo Supervisory Fishery Biologist Department of the Interior US Fish & Wildlife Service California, USA ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.