eCDF with confidence intervals
ecdf_fun(x, CI = TRUE, CI.interval = 0.95)numeric vector of the observations for ecdf; for the methods, an object inheriting from class "ecdf".
If TRUE CDF confidence intervals will be calculated; default is set to TRUE.
Confidence interval; default is set to 0.95
Compute an empirical cumulative distribution function, returns a data frame with value and proporiton. Code based on base eCDF function.
set.seed(12)
test<-rnorm(100)
ecdf_fun(test)
#> value proportion lwr.CI upr.CI
#> 1 -2.149260002 0.01 0.000000000 0.1458102
#> 2 -1.997642097 0.02 0.000000000 0.1558102
#> 3 -1.595625656 0.03 0.000000000 0.1658102
#> 4 -1.480567595 0.04 0.000000000 0.1758102
#> 5 -1.314272797 0.05 0.000000000 0.1858102
#> 6 -1.293882298 0.06 0.000000000 0.1958102
#> 7 -1.274059551 0.07 0.000000000 0.2058102
#> 8 -1.271053787 0.08 0.000000000 0.2158102
#> 9 -1.155992890 0.09 0.000000000 0.2258102
#> 10 -1.070492158 0.10 0.000000000 0.2358102
#> 11 -1.050890062 0.11 0.000000000 0.2458102
#> 12 -1.025244839 0.12 0.000000000 0.2558102
#> 13 -1.007298960 0.13 0.000000000 0.2658102
#> 14 -1.004451202 0.14 0.004189848 0.2758102
#> 15 -0.984673797 0.15 0.014189848 0.2858102
#> 16 -0.977053283 0.16 0.024189848 0.2958102
#> 17 -0.963398332 0.17 0.034189848 0.3058102
#> 18 -0.956744479 0.18 0.044189848 0.3158102
#> 19 -0.920005248 0.19 0.054189848 0.3258102
#> 20 -0.779566508 0.20 0.064189848 0.3358102
#> 21 -0.777719582 0.21 0.074189848 0.3458102
#> 22 -0.703464254 0.22 0.084189848 0.3558102
#> 23 -0.694737942 0.23 0.094189848 0.3658102
#> 24 -0.633838203 0.24 0.104189848 0.3758102
#> 25 -0.628255237 0.25 0.114189848 0.3858102
#> 26 -0.541888860 0.26 0.124189848 0.3958102
#> 27 -0.541028649 0.27 0.134189848 0.4058102
#> 28 -0.525400626 0.28 0.144189848 0.4158102
#> 29 -0.492599111 0.29 0.154189848 0.4258102
#> 30 -0.485141355 0.30 0.164189848 0.4358102
#> 31 -0.479512562 0.31 0.174189848 0.4458102
#> 32 -0.429406611 0.32 0.184189848 0.4558102
#> 33 -0.383950394 0.33 0.194189848 0.4658102
#> 34 -0.372456732 0.34 0.204189848 0.4758102
#> 35 -0.342289274 0.35 0.214189848 0.4858102
#> 36 -0.315348711 0.36 0.224189848 0.4958102
#> 37 -0.308503656 0.37 0.234189848 0.5058102
#> 38 -0.302459245 0.38 0.244189848 0.5158102
#> 39 -0.293305149 0.39 0.254189848 0.5258102
#> 40 -0.272296044 0.40 0.264189848 0.5358102
#> 41 -0.267384830 0.41 0.274189848 0.5458102
#> 42 -0.250038722 0.42 0.284189848 0.5558102
#> 43 -0.239013591 0.43 0.294189848 0.5658102
#> 44 -0.202110338 0.44 0.304189848 0.5758102
#> 45 -0.199105661 0.45 0.314189848 0.5858102
#> 46 -0.182519622 0.46 0.324189848 0.5958102
#> 47 -0.177968544 0.47 0.334189848 0.6058102
#> 48 -0.176724455 0.48 0.344189848 0.6158102
#> 49 -0.152416238 0.49 0.354189848 0.6258102
#> 50 -0.112670576 0.50 0.364189848 0.6358102
#> 51 -0.106463885 0.51 0.374189848 0.6458102
#> 52 -0.103310466 0.52 0.384189848 0.6558102
#> 53 -0.042684912 0.53 0.394189848 0.6658102
#> 54 -0.023379409 0.54 0.404189848 0.6758102
#> 55 0.004258039 0.55 0.414189848 0.6858102
#> 56 0.011951759 0.56 0.424189848 0.6958102
#> 57 0.104984233 0.57 0.434189848 0.7058102
#> 58 0.129262533 0.58 0.444189848 0.7158102
#> 59 0.131122595 0.59 0.454189848 0.7258102
#> 60 0.145799896 0.60 0.464189848 0.7358102
#> 61 0.189997859 0.61 0.474189848 0.7458102
#> 62 0.197128917 0.62 0.484189848 0.7558102
#> 63 0.223641415 0.63 0.494189848 0.7658102
#> 64 0.250320103 0.64 0.504189848 0.7758102
#> 65 0.274784178 0.65 0.514189848 0.7858102
#> 66 0.314204596 0.66 0.524189848 0.7958102
#> 67 0.340512271 0.67 0.534189848 0.8058102
#> 68 0.362064721 0.68 0.544189848 0.8158102
#> 69 0.376448400 0.69 0.554189848 0.8258102
#> 70 0.406546694 0.70 0.564189848 0.8358102
#> 71 0.428014802 0.71 0.574189848 0.8458102
#> 72 0.449465922 0.72 0.584189848 0.8558102
#> 73 0.452281257 0.73 0.594189848 0.8658102
#> 74 0.456827248 0.74 0.604189848 0.8758102
#> 75 0.506968172 0.75 0.614189848 0.8858102
#> 76 0.516755802 0.76 0.624189848 0.8958102
#> 77 0.539249744 0.77 0.634189848 0.9058102
#> 78 0.578134627 0.78 0.644189848 0.9158102
#> 79 0.673981164 0.79 0.654189848 0.9258102
#> 80 0.731453357 0.80 0.664189848 0.9358102
#> 81 0.734652106 0.81 0.674189848 0.9458102
#> 82 0.798105326 0.82 0.684189848 0.9558102
#> 83 0.834325038 0.83 0.694189848 0.9658102
#> 84 0.846790152 0.84 0.704189848 0.9758102
#> 85 0.855768432 0.85 0.714189848 0.9858102
#> 86 0.897156750 0.86 0.724189848 0.9958102
#> 87 0.897559402 0.87 0.734189848 1.0000000
#> 88 0.971120270 0.88 0.744189848 1.0000000
#> 89 0.994420600 0.89 0.754189848 1.0000000
#> 90 1.011979118 0.90 0.764189848 1.0000000
#> 91 1.033702981 0.91 0.774189848 1.0000000
#> 92 1.113709078 0.92 0.784189848 1.0000000
#> 93 1.145061573 0.93 0.794189848 1.0000000
#> 94 1.164465880 0.94 0.804189848 1.0000000
#> 95 1.188879156 0.95 0.814189848 1.0000000
#> 96 1.577169472 0.96 0.824189848 1.0000000
#> 97 1.954105255 0.97 0.834189848 1.0000000
#> 98 2.007201457 0.98 0.844189848 1.0000000
#> 99 2.020334842 0.99 0.854189848 1.0000000
#> 100 2.072035768 1.00 0.864189848 1.0000000