Another way to show the local truncation error for this method is to derive it, keeping track of the remainder terms as we go along. Once the numerical formula is derived, whatever error terms are left hanging around in the end will be the local truncation error. The idea was to start with a second order Taylor expansion: y(t n+1) = y(t. This error formula can be derived through an application of Taylor’s theorem or the Newton form of the linear interpolation error. The general trapezoidal rule T n(f) was obtained by applying the simple trapezoidal rule to a subdivision of the original interval of integration. Recall the notation h = b a n; x. (mathematics) a miscalculation that results from cutting off a numerical calculation before it is finished Familiarity information: TRUNCATION ERROR used as a noun is very rare. You can use this calculator to solve first-degree differential equation with a given initial value using the Runge-Kutta method AKA classic Runge-Kutta method (because there is a family of Runge-Kutta methods) or RK4 (because it is a fourth-order method). To use this method, you should have differential equation in the form. Chapter Objectives (2/2). Recognizing that truncation errors occur when exact mathematical formulations are represented by approximations. Knowing how to use the Taylor series to estimate.
In numerical analysis and scientific computing, truncation error is the error made by truncating an infinite sum and approximating it by a finite sum. For instance, if we approximate the sine function by the first two non-zero term of its Taylor series, as in for small , the resulting error is a truncation error. It is present even with infinite-precision arithmetic, because it is caused by truncation of the infinite Taylor series to form the algorithm.
Often, truncation error also includes discretization error, which is the error that arises from taking a finite number of steps in a computation to approximate an infinite process. For example, in numerical methods for ordinary differential equations, the continuously varying function that is the solution of the differential equation is approximated by a process that progresses step by step, and the error that this entails is a discretization or truncation error. See Truncation error (numerical integration) for more on this.
Occasionally, round-off error (the consequence of using finite precision floating point numbers on computers) is also called truncation error, especially if the number is rounded by truncation.
See also[edit]
Truncation Error Definition
References[edit]
- Atkinson, Kendall E. (1989), An Introduction to Numerical Analysis (2nd ed.), New York: John Wiley & Sons, p. 20, ISBN978-0-471-50023-0
- Stoer, Josef; Bulirsch, Roland (2002), Introduction to Numerical Analysis (3rd ed.), Berlin, New York: Springer-Verlag, p. 1, ISBN978-0-387-95452-3.
About Error Function Calculator
The Error Function Calculator is used to calculate the error function of a given number.
Error Function
In mathematics, the error function is a special function (non-elementary) of sigmoid shape, which occurs in probability, statistics and partial differential equations. It is also called the Gauss error function or probability integral.
Truncation Error Formula
The error function is defined as:
Error Function Table
The following is the error function and complementary error function table that shows the values of erf(x) and erfc(x) for x ranging from 0 to 3.5 with an increment of 0.01.x | erf(x) | erfc(x) |
---|---|---|
0.0 | 0.0 | 1.0 |
0.01 | 0.011283416 | 0.988716584 |
0.02 | 0.022564575 | 0.977435425 |
0.03 | 0.033841222 | 0.966158778 |
0.04 | 0.045111106 | 0.954888894 |
0.05 | 0.056371978 | 0.943628022 |
0.06 | 0.067621594 | 0.932378406 |
0.07 | 0.07885772 | 0.92114228 |
0.08 | 0.090078126 | 0.909921874 |
0.09 | 0.101280594 | 0.898719406 |
0.1 | 0.112462916 | 0.887537084 |
0.11 | 0.123622896 | 0.876377104 |
0.12 | 0.134758352 | 0.865241648 |
0.13 | 0.145867115 | 0.854132885 |
0.14 | 0.156947033 | 0.843052967 |
0.15 | 0.167995971 | 0.832004029 |
0.16 | 0.179011813 | 0.820988187 |
0.17 | 0.189992461 | 0.810007539 |
0.18 | 0.200935839 | 0.799064161 |
0.19 | 0.211839892 | 0.788160108 |
0.2 | 0.222702589 | 0.777297411 |
0.21 | 0.233521923 | 0.766478077 |
0.22 | 0.244295912 | 0.755704088 |
0.23 | 0.2550226 | 0.7449774 |
0.24 | 0.265700059 | 0.734299941 |
0.25 | 0.27632639 | 0.72367361 |
0.26 | 0.286899723 | 0.713100277 |
0.27 | 0.297418219 | 0.702581781 |
0.28 | 0.307880068 | 0.692119932 |
0.29 | 0.318283496 | 0.681716504 |
0.3 | 0.328626759 | 0.671373241 |
0.31 | 0.33890815 | 0.66109185 |
0.32 | 0.349125995 | 0.650874005 |
0.33 | 0.359278655 | 0.640721345 |
0.34 | 0.369364529 | 0.630635471 |
0.35 | 0.379382054 | 0.620617946 |
0.36 | 0.389329701 | 0.610670299 |
0.37 | 0.399205984 | 0.600794016 |
0.38 | 0.409009453 | 0.590990547 |
0.39 | 0.4187387 | 0.5812613 |
0.4 | 0.428392355 | 0.571607645 |
0.41 | 0.43796909 | 0.56203091 |
0.42 | 0.447467618 | 0.552532382 |
0.43 | 0.456886695 | 0.543113305 |
0.44 | 0.466225115 | 0.533774885 |
0.45 | 0.47548172 | 0.52451828 |
0.46 | 0.48465539 | 0.51534461 |
0.47 | 0.493745051 | 0.506254949 |
0.48 | 0.502749671 | 0.497250329 |
0.49 | 0.511668261 | 0.488331739 |
0.5 | 0.520499878 | 0.479500122 |
0.51 | 0.52924362 | 0.47075638 |
0.52 | 0.53789863 | 0.46210137 |
0.53 | 0.546464097 | 0.453535903 |
0.54 | 0.55493925 | 0.44506075 |
0.55 | 0.563323366 | 0.436676634 |
0.56 | 0.571615764 | 0.428384236 |
0.57 | 0.579815806 | 0.420184194 |
0.58 | 0.5879229 | 0.4120771 |
0.59 | 0.595936497 | 0.404063503 |
0.6 | 0.603856091 | 0.396143909 |
0.61 | 0.611681219 | 0.388318781 |
0.62 | 0.619411462 | 0.380588538 |
0.63 | 0.627046443 | 0.372953557 |
0.64 | 0.634585829 | 0.365414171 |
0.65 | 0.642029327 | 0.357970673 |
0.66 | 0.649376688 | 0.350623312 |
0.67 | 0.656627702 | 0.343372298 |
0.68 | 0.663782203 | 0.336217797 |
0.69 | 0.670840062 | 0.329159938 |
0.7 | 0.677801194 | 0.322198806 |
0.71 | 0.68466555 | 0.31533445 |
0.72 | 0.691433123 | 0.308566877 |
0.73 | 0.698103943 | 0.301896057 |
0.74 | 0.704678078 | 0.295321922 |
0.75 | 0.711155634 | 0.288844366 |
0.76 | 0.717536753 | 0.282463247 |
0.77 | 0.723821614 | 0.276178386 |
0.78 | 0.730010431 | 0.269989569 |
0.79 | 0.736103454 | 0.263896546 |
0.8 | 0.742100965 | 0.257899035 |
0.81 | 0.748003281 | 0.251996719 |
0.82 | 0.753810751 | 0.246189249 |
0.83 | 0.759523757 | 0.240476243 |
0.84 | 0.765142711 | 0.234857289 |
0.85 | 0.770668058 | 0.229331942 |
0.86 | 0.776100268 | 0.223899732 |
0.87 | 0.781439845 | 0.218560155 |
0.88 | 0.786687319 | 0.213312681 |
0.89 | 0.791843247 | 0.208156753 |
0.9 | 0.796908212 | 0.203091788 |
0.91 | 0.801882826 | 0.198117174 |
0.92 | 0.806767722 | 0.193232278 |
0.93 | 0.811563559 | 0.188436441 |
0.94 | 0.816271019 | 0.183728981 |
0.95 | 0.820890807 | 0.179109193 |
0.96 | 0.82542365 | 0.17457635 |
0.97 | 0.829870293 | 0.170129707 |
0.98 | 0.834231504 | 0.165768496 |
0.99 | 0.83850807 | 0.16149193 |
1.0 | 0.842700793 | 0.157299207 |
1.01 | 0.846810496 | 0.153189504 |
1.02 | 0.850838018 | 0.149161982 |
1.03 | 0.854784211 | 0.145215789 |
1.04 | 0.858649947 | 0.141350053 |
1.05 | 0.862436106 | 0.137563894 |
1.06 | 0.866143587 | 0.133856413 |
1.07 | 0.869773297 | 0.130226703 |
1.08 | 0.873326158 | 0.126673842 |
1.09 | 0.876803102 | 0.123196898 |
1.1 | 0.88020507 | 0.11979493 |
1.11 | 0.883533012 | 0.116466988 |
1.12 | 0.88678789 | 0.11321211 |
1.13 | 0.88997067 | 0.11002933 |
1.14 | 0.893082328 | 0.106917672 |
1.15 | 0.896123843 | 0.103876157 |
1.16 | 0.899096203 | 0.100903797 |
1.17 | 0.902000399 | 0.097999601 |
1.18 | 0.904837427 | 0.095162573 |
1.19 | 0.907608286 | 0.092391714 |
1.2 | 0.910313978 | 0.089686022 |
1.21 | 0.912955508 | 0.087044492 |
1.22 | 0.915533881 | 0.084466119 |
1.23 | 0.918050104 | 0.081949896 |
1.24 | 0.920505184 | 0.079494816 |
1.25 | 0.922900128 | 0.077099872 |
1.26 | 0.925235942 | 0.074764058 |
1.27 | 0.927513629 | 0.072486371 |
1.28 | 0.929734193 | 0.070265807 |
1.29 | 0.931898633 | 0.068101367 |
1.3 | 0.934007945 | 0.065992055 |
1.31 | 0.936063123 | 0.063936877 |
1.32 | 0.938065155 | 0.061934845 |
1.33 | 0.940015026 | 0.059984974 |
1.34 | 0.941913715 | 0.058086285 |
1.35 | 0.943762196 | 0.056237804 |
1.36 | 0.945561437 | 0.054438563 |
1.37 | 0.947312398 | 0.052687602 |
1.38 | 0.949016035 | 0.050983965 |
1.39 | 0.950673296 | 0.049326704 |
1.4 | 0.95228512 | 0.04771488 |
1.41 | 0.953852439 | 0.046147561 |
1.42 | 0.955376179 | 0.044623821 |
1.43 | 0.956857253 | 0.043142747 |
1.44 | 0.95829657 | 0.04170343 |
1.45 | 0.959695026 | 0.040304974 |
1.46 | 0.96105351 | 0.03894649 |
1.47 | 0.9623729 | 0.0376271 |
1.48 | 0.963654065 | 0.036345935 |
1.49 | 0.964897865 | 0.035102135 |
1.5 | 0.966105146 | 0.033894854 |
1.51 | 0.967276748 | 0.032723252 |
1.52 | 0.968413497 | 0.031586503 |
1.53 | 0.969516209 | 0.030483791 |
1.54 | 0.97058569 | 0.02941431 |
1.55 | 0.971622733 | 0.028377267 |
1.56 | 0.972628122 | 0.027371878 |
1.57 | 0.973602627 | 0.026397373 |
1.58 | 0.974547009 | 0.025452991 |
1.59 | 0.975462016 | 0.024537984 |
1.6 | 0.976348383 | 0.023651617 |
1.61 | 0.977206837 | 0.022793163 |
1.62 | 0.978038088 | 0.021961912 |
1.63 | 0.97884284 | 0.02115716 |
1.64 | 0.97962178 | 0.02037822 |
1.65 | 0.980375585 | 0.019624415 |
1.66 | 0.981104921 | 0.018895079 |
1.67 | 0.981810442 | 0.018189558 |
1.68 | 0.982492787 | 0.017507213 |
1.69 | 0.983152587 | 0.016847413 |
1.7 | 0.983790459 | 0.016209541 |
1.71 | 0.984407008 | 0.015592992 |
1.72 | 0.985002827 | 0.014997173 |
1.73 | 0.9855785 | 0.0144215 |
1.74 | 0.986134595 | 0.013865405 |
1.75 | 0.986671671 | 0.013328329 |
1.76 | 0.987190275 | 0.012809725 |
1.77 | 0.987690942 | 0.012309058 |
1.78 | 0.988174196 | 0.011825804 |
1.79 | 0.988640549 | 0.011359451 |
1.8 | 0.989090502 | 0.010909498 |
1.81 | 0.989524545 | 0.010475455 |
1.82 | 0.989943156 | 0.010056844 |
1.83 | 0.990346805 | 0.009653195 |
1.84 | 0.990735948 | 0.009264052 |
1.85 | 0.99111103 | 0.00888897 |
1.86 | 0.991472488 | 0.008527512 |
1.87 | 0.991820748 | 0.008179252 |
1.88 | 0.992156223 | 0.007843777 |
1.89 | 0.992479318 | 0.007520682 |
1.9 | 0.992790429 | 0.007209571 |
1.91 | 0.99308994 | 0.00691006 |
1.92 | 0.993378225 | 0.006621775 |
1.93 | 0.99365565 | 0.00634435 |
1.94 | 0.993922571 | 0.006077429 |
1.95 | 0.994179334 | 0.005820666 |
1.96 | 0.994426275 | 0.005573725 |
1.97 | 0.994663725 | 0.005336275 |
1.98 | 0.994892 | 0.005108 |
1.99 | 0.995111413 | 0.004888587 |
2.0 | 0.995322265 | 0.004677735 |
2.01 | 0.995524849 | 0.004475151 |
2.02 | 0.995719451 | 0.004280549 |
2.03 | 0.995906348 | 0.004093652 |
2.04 | 0.99608581 | 0.00391419 |
2.05 | 0.996258096 | 0.003741904 |
2.06 | 0.996423462 | 0.003576538 |
2.07 | 0.996582153 | 0.003417847 |
2.08 | 0.996734409 | 0.003265591 |
2.09 | 0.996880461 | 0.003119539 |
2.1 | 0.997020533 | 0.002979467 |
2.11 | 0.997154845 | 0.002845155 |
2.12 | 0.997283607 | 0.002716393 |
2.13 | 0.997407023 | 0.002592977 |
2.14 | 0.997525293 | 0.002474707 |
2.15 | 0.997638607 | 0.002361393 |
2.16 | 0.997747152 | 0.002252848 |
2.17 | 0.997851108 | 0.002148892 |
2.18 | 0.997950649 | 0.002049351 |
2.19 | 0.998045943 | 0.001954057 |
2.2 | 0.998137154 | 0.001862846 |
2.21 | 0.998224438 | 0.001775562 |
2.22 | 0.998307948 | 0.001692052 |
2.23 | 0.998387832 | 0.001612168 |
2.24 | 0.998464231 | 0.001535769 |
2.25 | 0.998537283 | 0.001462717 |
2.26 | 0.998607121 | 0.001392879 |
2.27 | 0.998673872 | 0.001326128 |
2.28 | 0.998737661 | 0.001262339 |
2.29 | 0.998798606 | 0.001201394 |
2.3 | 0.998856823 | 0.001143177 |
2.31 | 0.998912423 | 0.001087577 |
2.32 | 0.998965513 | 0.001034487 |
2.33 | 0.999016195 | 0.000983805 |
2.34 | 0.99906457 | 0.00093543 |
2.35 | 0.999110733 | 0.000889267 |
2.36 | 0.999154777 | 0.000845223 |
2.37 | 0.99919679 | 0.00080321 |
2.38 | 0.999236858 | 0.000763142 |
2.39 | 0.999275064 | 0.000724936 |
2.4 | 0.999311486 | 0.000688514 |
2.41 | 0.999346202 | 0.000653798 |
2.42 | 0.999379283 | 0.000620717 |
2.43 | 0.999410802 | 0.000589198 |
2.44 | 0.999440826 | 0.000559174 |
2.45 | 0.99946942 | 0.00053058 |
2.46 | 0.999496646 | 0.000503354 |
2.47 | 0.999522566 | 0.000477434 |
2.48 | 0.999547236 | 0.000452764 |
2.49 | 0.999570712 | 0.000429288 |
2.5 | 0.999593048 | 0.000406952 |
2.51 | 0.999614295 | 0.000385705 |
2.52 | 0.999634501 | 0.000365499 |
2.53 | 0.999653714 | 0.000346286 |
2.54 | 0.999671979 | 0.000328021 |
2.55 | 0.99968934 | 0.00031066 |
2.56 | 0.999705837 | 0.000294163 |
2.57 | 0.999721511 | 0.000278489 |
2.58 | 0.9997364 | 0.0002636 |
2.59 | 0.999750539 | 0.000249461 |
2.6 | 0.999763966 | 0.000236034 |
2.61 | 0.999776711 | 0.000223289 |
2.62 | 0.999788809 | 0.000211191 |
2.63 | 0.999800289 | 0.000199711 |
2.64 | 0.999811181 | 0.000188819 |
2.65 | 0.999821512 | 0.000178488 |
2.66 | 0.999831311 | 0.000168689 |
2.67 | 0.999840601 | 0.000159399 |
2.68 | 0.999849409 | 0.000150591 |
2.69 | 0.999857757 | 0.000142243 |
2.7 | 0.999865667 | 0.000134333 |
2.71 | 0.999873162 | 0.000126838 |
2.72 | 0.999880261 | 0.000119739 |
2.73 | 0.999886985 | 0.000113015 |
2.74 | 0.999893351 | 0.000106649 |
2.75 | 0.999899378 | 0.000100622 |
2.76 | 0.999905082 | 9.4918e-05 |
2.77 | 0.99991048 | 8.952e-05 |
2.78 | 0.999915587 | 8.4413e-05 |
2.79 | 0.999920418 | 7.9582e-05 |
2.8 | 0.999924987 | 7.5013e-05 |
2.81 | 0.999929307 | 7.0693e-05 |
2.82 | 0.99993339 | 6.661e-05 |
2.83 | 0.99993725 | 6.275e-05 |
2.84 | 0.999940898 | 5.9102e-05 |
2.85 | 0.999944344 | 5.5656e-05 |
2.86 | 0.999947599 | 5.2401e-05 |
2.87 | 0.999950673 | 4.9327e-05 |
2.88 | 0.999953576 | 4.6424e-05 |
2.89 | 0.999956316 | 4.3684e-05 |
2.9 | 0.999958902 | 4.1098e-05 |
2.91 | 0.999961343 | 3.8657e-05 |
2.92 | 0.999963645 | 3.6355e-05 |
2.93 | 0.999965817 | 3.4183e-05 |
2.94 | 0.999967866 | 3.2134e-05 |
2.95 | 0.999969797 | 3.0203e-05 |
2.96 | 0.999971618 | 2.8382e-05 |
2.97 | 0.999973334 | 2.6666e-05 |
2.98 | 0.999974951 | 2.5049e-05 |
2.99 | 0.999976474 | 2.3526e-05 |
3.0 | 0.99997791 | 2.209e-05 |
3.01 | 0.999979261 | 2.0739e-05 |
3.02 | 0.999980534 | 1.9466e-05 |
3.03 | 0.999981732 | 1.8268e-05 |
3.04 | 0.999982859 | 1.7141e-05 |
3.05 | 0.99998392 | 1.608e-05 |
3.06 | 0.999984918 | 1.5082e-05 |
3.07 | 0.999985857 | 1.4143e-05 |
3.08 | 0.99998674 | 1.326e-05 |
3.09 | 0.999987571 | 1.2429e-05 |
3.1 | 0.999988351 | 1.1649e-05 |
3.11 | 0.999989085 | 1.0915e-05 |
3.12 | 0.999989774 | 1.0226e-05 |
3.13 | 0.999990422 | 9.578e-06 |
3.14 | 0.99999103 | 8.97e-06 |
3.15 | 0.999991602 | 8.398e-06 |
3.16 | 0.999992138 | 7.862e-06 |
3.17 | 0.999992642 | 7.358e-06 |
3.18 | 0.999993115 | 6.885e-06 |
3.19 | 0.999993558 | 6.442e-06 |
3.2 | 0.999993974 | 6.026e-06 |
3.21 | 0.999994365 | 5.635e-06 |
3.22 | 0.999994731 | 5.269e-06 |
3.23 | 0.999995074 | 4.926e-06 |
3.24 | 0.999995396 | 4.604e-06 |
3.25 | 0.999995697 | 4.303e-06 |
3.26 | 0.99999598 | 4.02e-06 |
3.27 | 0.999996245 | 3.755e-06 |
3.28 | 0.999996493 | 3.507e-06 |
3.29 | 0.999996725 | 3.275e-06 |
3.3 | 0.999996942 | 3.058e-06 |
3.31 | 0.999997146 | 2.854e-06 |
3.32 | 0.999997336 | 2.664e-06 |
3.33 | 0.999997515 | 2.485e-06 |
3.34 | 0.999997681 | 2.319e-06 |
3.35 | 0.999997838 | 2.162e-06 |
3.36 | 0.999997983 | 2.017e-06 |
3.37 | 0.99999812 | 1.88e-06 |
3.38 | 0.999998247 | 1.753e-06 |
3.39 | 0.999998367 | 1.633e-06 |
3.4 | 0.999998478 | 1.522e-06 |
3.41 | 0.999998582 | 1.418e-06 |
3.42 | 0.999998679 | 1.321e-06 |
3.43 | 0.99999877 | 1.23e-06 |
3.44 | 0.999998855 | 1.145e-06 |
3.45 | 0.999998934 | 1.066e-06 |
3.46 | 0.999999008 | 9.92e-07 |
3.47 | 0.999999077 | 9.23e-07 |
3.48 | 0.999999141 | 8.59e-07 |
3.49 | 0.999999201 | 7.99e-07 |
3.5 | 0.999999257 | 7.43e-07 |