How can I plot data with confidence intervals

Question

If I have 10 values  each of which has a fitted value F  and an upper and lower confidence interval U and L   set seed 0815  F  lt - runif 10  1  2   L  lt - runif 10  0  1  U  lt - runif 10  2  3    How can I show these 10 fitted values and their confidence intervals in the same plot like the one below in R

User · Answer

Some addition to the previous answers  It is nice to regulate the density of the polygon to avoid obscuring the data points   library MASS  attach Boston  lm fit2   lm medv poly lstat 2   plot lstat medv  new lstat   seq min lstat   max lstat   length out 100  preds  lt - predict lm fit2  newdata   data frame lstat new lstat   interval    prediction   lines sort lstat   fitted lm fit2  order lstat    col  red   lwd 3   polygon c rev new lstat   new lstat   c rev preds   3    preds   2    density 10  col    blue   border   NA  lines new lstat  preds   3   lty    dashed   col    red   lines new lstat  preds   2   lty    dashed   col    red       Please note that you see the prediction interval on the picture  which is several times wider than the confidence interval  You can read here the detailed explanation of those two types of interval estimates

User · Answer

Here is a solution using functions plot    polygon   and lines      set seed 1234   df  lt - data frame x  1 10                   F  runif 10 1 2                    L  runif 10 0 1                    U  runif 10 2 3      plot df x  df F  ylim   c 0 4   type    l     make polygon where coordinates start with lower limit and     then upper limit in reverse order  polygon c df x rev df x   c df L rev df U   col    grey75   border   FALSE   lines df x  df F  lwd   2    add red lines on borders of polygon  lines df x  df U  col  red  lty 2   lines df x  df L  col  red  lty 2      Now use example data provided by OP in another question      Lower  lt - c 0 418116841  0 391011834  0 393297710          0 366144073 0 569956636 0 224775521 0 599166016 0 512269587          0 531378573  0 311448219  0 392045751 0 153614913  0 366684097          0 161100849 0 700274810 0 629714150  0 661641288  0 533404093          0 412427559  0 432905333  0 525306427 0 224292061          0 28893064 0 099543648  0 342995605 0 086973739 0 289030388          0 081230826 0 164505624  -0 031290586 0 148383474 0 070517523 0 009686605          -0 052703529 0 475924192 0 253382210  0 354011010 0 130295355 0 102253218          0 446598823 0 548330752 0 393985810 0 481691632 0 111811248 0 339626541          0 267831909 0 133460254 0 347996621 0 412472322 0 133671128 0 178969601 0 484070587          0 335833224 0 037258467  0 141312363 0 361392799 0 129791998          0 283759439 0 333893418 0 569533076 0 385258093 0 356201955 0 481816148          0 531282473 0 273126565 0 267815691 0 138127486 0 008865700 0 018118398 0 080143484          0 117861634 0 073697418 0 230002398 0 105855042 0 262367348 0 217799352 0 289108011          0 161271889 0 219663224 0 306117717 0 538088622 0 320711912 0 264395149 0 396061543          0 397350946 0 151726970 0 048650180 0 131914718 0 076629840 0 425849394          0 068692279 0 155144797 0 137939059 0 301912657 -0 071415593 -0 030141781 0 119450922          0 312927614 0 231345972    Upper limit  lt - c 0 6446223 0 6177311  0 6034427  0 5726503        0 7644718  0 4585430  0 8205418  0 7154043 0 7370033        0 5285199  0 5973728  0 3764209  0 5818298        0 3960867 0 8972357  0 8370151  0 8359921  0 7449118        0 6152879  0 6200704  0 7041068  0 4541011  0 5222653        0 3472364  0 5956551  0 3068065  0 5112895  0 3081448        0 3745473  0 1931089  0 3890704  0 3031025  0 2472591        0 1976092  0 6906118  0 4736644  0 5770463  0 3528607        0 3307651  0 6681629  0 7476231  0 5959025  0 7128883        0 3451623  0 5609742  0 4739216  0 3694883  0 5609220        0 6343219  0 3647751  0 4247147  0 6996334  0 5562876        0 2586490  0 3750040  0 5922248  0 3626322  0 5243285        0 5548211  0 7409648  0 5820070  0 5530232  0 6863703        0 7206998  0 4952387  0 4993264  0 3527727  0 2203694        0 2583149  0 3035342  0 3462009  0 3003602  0 4506054        0 3359478  0 4834151  0 4391330  0 5273411  0 3947622        0 4133769  0 5288060  0 7492071  0 5381701  0 4825456        0 6121942  0 6192227  0 3784870  0 2574025  0 3704140        0 2945623  0 6532694  0 2697202  0 3652230  0 3696383        0 5268808  0 1545602  0 2221450  0 3553377  0 5204076        0 3550094     Fitted values lt - c 0 53136955  0 50437146  0 49837019    0 46939721  0 66721423  0 34165926  0 70985388  0 61383696    0 63419092  0 41998407  0 49470927  0 26501789  0 47425695    0 27859380  0 79875525  0 73336461  0 74881668  0 63915795    0 51385774  0 52648789  0 61470661  0 33919656  0 40559797    0 22339000  0 46932536  0 19689011  0 40015996  0 19468781    0 26952645  0 08090917  0 26872696  0 18680999  0 12847285    0 07245286  0 58326799  0 36352329  0 46552867  0 24157804    0 21650915  0 55738088  0 64797691  0 49494416  0 59728999    0 22848680  0 45030036  0 37087676  0 25147426  0 45445930    0 52339711  0 24922310  0 30184215  0 59185198  0 44606040    0 14795374  0 25815819  0 47680880  0 24621212  0 40404398    0 44435727  0 65524894  0 48363255  0 45461258  0 58409323    0 62599114  0 38418264  0 38357103  0 24545011  0 11461756    0 13821664  0 19183886  0 23203127  0 18702881  0 34030391    0 22090140  0 37289121  0 32846615  0 40822456  0 27801706    0 31652008  0 41746184  0 64364785  0 42944100  0 37347037    0 50412786  0 50828681  0 26510696  0 15302635  0 25116438    0 18559609  0 53955941  0 16920626  0 26018389  0 25378867    0 41439675  0 04157232  0 09600163  0 23739430  0 41666762    0 29317767    Assemble into a data frame  no x provided  so using indices    df2  lt - data frame x seq length Fitted values                        fit Fitted values lwr Lower upr Upper limit   plot fit x data df2 ylim range c df2 lwr df2 upr      make polygon where coordinates start with lower limit and then upper limit in reverse order  with df2 polygon c x rev x   c lwr rev upr   col    grey75   border   FALSE    matlines df2  1  df2  -1             lwd c 2 1 1             lty 1            col c  black   red   red

User · Answer

Here is part of my program related to plotting confidence interval   1  Generate the test data  ads   1 require stats   require graphics  library splines  x raw  lt - seq 1 10 0 1  y  lt - cos x raw  rnorm len data 0 0 1  y 30   lt - 1 4   outlier point len data   length x raw  N  lt - len data summary fm1  lt - lm y bs x raw  df 5   model   TRUE  x  T  y   T   ht  lt -seq 1 10 length out   len data  plot x   x raw  y   y type    p   y e  lt - predict fm1  data frame height   ht   lines x  ht  y   y e    Result    2  Fitting the raw data using B-spline smoother method  sigma e  lt - sqrt sum  y-y e  2  N  print sigma e  H lt -fm1 x A  lt -solve t H      H  y e minus  lt - rep 0 N  y e plus  lt - rep 0 N  y e minus N  for  i in 1 N        tmp  lt -t matrix H i         A     matrix H i        tmp  lt - 1 96 sqrt tmp      y e minus i   lt - y e i  - tmp     y e plus i   lt - y e i    tmp   plot x   x raw  y   y type    p   polygon c ht rev ht   c y e minus rev y e plus   col   rgb 1  0  0 0 5   border   NA   plot x   x raw  y   y type    p   lines x  ht  y   y e plus  lty    dashed   col    red   lines x  ht  y   y e  lines x  ht  y   y e minus  lty    dashed   col    red     Result

User · Answer

Here is a plotrix solution   set seed 0815  x  lt - 1 10 F  lt - runif 10 1 2   L  lt - runif 10 0 1  U  lt - runif 10 2 3   require plotrix  plotCI x  F  ui U  li L      And here is a ggplot solution   set seed 0815  df  lt - data frame x  1 10                   F  runif 10 1 2                    L  runif 10 0 1                    U  runif 10 2 3    require ggplot2  ggplot df  aes x   x  y   F       geom point size   4      geom errorbar aes ymax   U  ymin   L       UPDATE  Here is a base solution to your edits   set seed 1234  x  lt - rnorm 20  df  lt - data frame x   x                   y   x   rnorm 20    plot y   x  data   df     model mod  lt - lm y   x  data   df     predicts   interval newx  lt - seq min df x   max df x   length out 100  preds  lt - predict mod  newdata   data frame x newx                     interval    confidence      plot plot y   x  data   df  type    n     add fill polygon c rev newx   newx   c rev preds   3    preds   2    col    grey80   border   NA    model abline mod    intervals lines newx  preds   3   lty    dashed   col    red   lines newx  preds   2   lty    dashed   col    red

[r] How can I plot data with confidence intervals?

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