Integral curve fitting in origin

In summary, integral curve fitting in Origin is a data analysis technique used to fit a mathematical curve to experimental data points. It involves finding the best-fit parameters of a mathematical function that can be integrated to fit the data. This technique is commonly used in physics, chemistry, and other scientific fields to analyze and model complex data sets. The process involves selecting a function, finding the best-fit parameters, and minimizing squared differences between data points and function values. Its advantages include handling complex data sets, estimating uncertainties, and providing a user-friendly interface. Origin offers a variety of built-in and customizable functions for fitting, making it suitable for both linear and non-linear data.
  • #1
`Pavol Namer
10
0
Dear users,

I deal with following problem.

I've got a data of Intenzity of chemiluminezcence as a function of temperature. The data should be fitted by following equation:

upload_2015-2-17_16-1-35.png


I found that in origin one can fit also data with integral function, with fittin parameters P, A, i, E.
The beta and R are constants that I already know.

So my question is. Is it possible to make this kind of curve fitting in Origin, and Is it correct to make this kind of curve fitting or it is impossible to obtain correct physical results.

Thank you in advance

PN
 

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  • #2
Hi ! Your question concerns the fitting of an "integral equation" to experimental data.
I cannot say, a-priori, if it's relevant to the kind of method used in the paper : https://fr.scribd.com/doc/14674814/Regressions-et-equations-intégrales
To answer to this question, it is important to know how the experimental data are distributed (regularly or non-regularly spaced, range, order of magnitude of scatter, ...).
If you post an example of data, I could check and say if the method described in the referenced paper can be addapted to become convenient in your case.
 
  • #3
Hi!
Thank you for your answer,
Of course, I can show you the data,

so, here's the plot of a data and data below
upload_2015-2-18_9-54-27.png


303,143 0,40355
303,143 0,88781
303,143 0,32284
303,143 0,64568
303,143 0,88781
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303,143 0,72639
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303,143 1,21065
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303,143 2,25989
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429,321 40,1937
429,486 43,98709
429,65 40,67797
429,815 43,50282
429,979 41,96933
430,143 43,98709
430,308 45,60129
430,472 44,0678
430,636 46,73123
430,801 51,49314
430,965 47,2155
431,129 49,47538
431,294 46,89266
431,458 51,57385
431,622 49,31396
431,787 50,60533
431,951 54,88297
432,115 52,38095
432,279 52,46166
432,444 56,33575
432,608 57,54641
432,772 60,37127
432,936 54,72155
433,1 57,38499
433,265 59,24132
433,429 57,30428
433,593 60,29056
433,757 62,06618
433,921 63,68039
434,085 65,29459
434,249 68,11945
434,414 64,97175
434,578 64,24536
434,742 68,84584
434,906 67,63519
435,07 69,3301
435,234 71,18644
435,398 70,37934
435,562 72,80065
435,726 76,67474
435,89 81,03309
436,054 73,93059
436,218 73,12349
436,382 79,09605
436,546 74,73769
436,71 81,9209
436,874 86,27926
437,038 84,82647
437,202 82,56659
437,366 89,50767
437,53 94,10815
437,694 91,12187
437,858 94,83454
438,022 93,94673
438,186 98,30508
438,35 99,03148
438,513 96,0452
438,677 95,39952
438,841 104,7619
439,005 105,08475
439,169 104,7619
439,333 107,82889
439,496 110,73446
439,66 108,23245
439,824 115,65779
439,988 115,65779
440,152 118,8862
440,315 120,90395
440,479 119,28975
440,643 118,72478
440,807 123,24455
440,97 124,53592
441,134 130,34705
441,298 130,10492
441,462 135,67393
441,625 133,17191
441,789 132,12268
441,953 140,75868
442,116 144,14851
442,28 149,55609
442,444 143,90638
442,607 150,68604
442,771 149,39467
442,934 158,59564
443,098 158,99919
443,262 156,49718
443,425 163,59968
443,589 164,24536
443,752 165,94027
443,916 170,13721
444,08 167,07022
444,243 179,4996
444,407 179,90315
444,57 178,45036
444,734 192,81679
444,897 190,5569
445,061 195,64165
445,224 198,14366
445,388 193,86602
445,551 199,83858
445,715 198,78935
445,878 196,93301
446,041 207,50605
446,205 221,2268
446,368 205,73043
446,532 213,96287
446,695 218,96691
446,858 215,98063
447,022 217,99839
447,185 218,15981
447,349 234,8749
447,512 230,26634
447,675 241,64649
447,839 232,92978
448,002 244,8749
448,165 248,91041
448,329 252,7845
448,492 250,84746
448,655 257,70783
448,818 253,5109
448,982 253,10734
449,145 265,94027
449,308 263,92252
449,471 257,54641
449,635 283,53511
449,798 276,99758
449,961 291,52542
450,124 294,26957
450,287 287,4092
450,451 283,4544
450,614 286,19855
450,777 308,55529
450,94 298,14366
451,103 309,36239
451,266 310,49233
451,429 306,77966
451,593 318,0791
451,756 324,69734
451,919 322,841
452,082 322,841
452,245 337,69169
452,408 340,43584
452,571 342,5343
452,734 342,45359
452,897 354,88297
453,06 361,50121
453,223 360,77482
453,386 376,59403
453,549 377,9661
453,712 385,55287
453,875 386,11784
454,038 388,70056
454,201 414,68927
454,364 412,42938
454,527 412,75222
454,69 429,53995
454,853 439,79015
455,016 432,84907
455,179 452,62308
455,341 462,06618
455,504 462,954
455,667 480,79096
455,83 483,93866
455,993 495,2381
456,156 495,56094
456,319 504,19693
456,481 520,33898
456,644 536,31961
456,807 557,14286
456,97 556,33575
457,133 570,94431
457,295 576,3519
457,458 591,84826
457,621 595,88378
457,784 622,92171
457,946 622,27603
458,109 657,86925
458,272 664,32607
458,435 673,68846
458,597 687,48991
458,76 698,14366
458,923 720,5004
459,085 745,76271
459,248 762,63115
459,411 773,76917
459,573 785,23002
459,736 798,38579
459,898 810,16949
460,061 851,41243
460,24 861,82405
460,386 883,05085
460,549 896,20662
460,711 928,00646
460,874 942,85714
461,037 965,94027
461,215 991,92897
461,378 1026,55367
461,54 1031,63842
461,703 1068,44229
461,865 1073,12349
462,028 1099,1929
462,19 1117,91768
462,353 1132,76836
462,515 1142,13075
462,678 1203,38983
462,84 1220,5004
463,003 1234,54399
463,165 1256,98144
463,328 1267,47377
463,49 1285,95642
463,652 1323,80952
463,815 1345,84342
463,977 1335,51251
464,14 1351,08959
464,302 1384,74576
464,464 1387,97417
464,627 1431,71913
464,789 1431,88055
464,951 1464,5682
465,114 1464,5682
465,276 1472,55851
465,438 1490,07264
465,6 1511,21872
465,763 1528,00646
465,925 1540,51655
466,087 1582,80872
466,249 1564,81033
466,412 1595,15738
466,574 1613,15577
466,736 1623,56739
466,898 1636,40032
467,061 1671,50928
467,223 1674,41485
467,385 1682,48588
467,547 1706,86037
467,709 1757,4657
467,871 1768,20016
468,034 1780,06457
468,196 1766,66667
468,358 1815,98063
468,52 1812,75222
468,682 1829,78208
468,844 1864,89104
469,006 1859,48345
469,168 1883,53511
469,33 1887,00565
469,492 1899,03148
469,654 1955,52865
469,816 1970,54076
469,978 1954,56013
470,14 2005,40759
470,302 2013,47861
470,464 2045,52058
470,626 2077,159
470,788 2060,45198
470,95 2111,0573
471,112 2093,13963
471,274 2186,68281
471,436 2180,87167
471,598 2195,40032
471,76 2231,71913
471,922 2239,14447
472,084 2267,07022
472,246 2287,73204
472,408 2294,26957
472,57 2337,69169
472,731 2358,91848
472,893 2413,64003
473,055 2433,0912
473,063 2452,46166

I don't know if you mean this kind of data example, do you?
 
  • #4
At first sight, it doesn't work.
What is the value of Troom corresponding to the data ?
Is the unknown coefficient (A/i) negative ?
 
  • #5
Hi,
The Troom is the initial temperature so it start in first column Troo=303,143 Kelvin
A/i is pozitive parameter and parameter Beta is also pozitive (beta value is known, so it is not fit).

Thank you for your help.

P.

Here is a similar plot where the data was fitted on this type of file using equastion writes above
1-s2.0-S0141391010003496-gr1.jpg
 
  • #6
When T is increassing, the integral is increassing, the denominator of the function is increassing, the function is decreassing, which is not consistent with the data. This seems to be the main cause of failure of the fitting.
 
  • #7
Since the issue remained outstanding for enough time, I will close it, as far I am concerned.
I cannot help more because the function proposed is not convenient to fit with the given data : any fitting method fails if the general shape of the function is in contradiction with the experimental data.
This is clear on the joint figure : The 1080 experimental points are drawn on logarithmic scale. This is necessary to make visible the scatter in case of large range of magnitude.
The kind of shape of the functions I(T) is sketched (red curve) It is not possible to compute the values of the parameters because there is no experimental point in the convenient range. So, the curve drawn is purely symbolic, only for explanation.
Probably, reconsidering the physical model will lead to a more convenient function.

Figure.JPG
 
  • #8
I´m so sorry, that I haven't replied earlier. Thank you for sharing your answer, but If you look at my first contribution you have used different formula from my formula in your plot. The denominator is power of 2. But you are right this function has decrease character. And therefore we have to used different physical model.

Thank's a lot for your time, and again I am very sorry that I haven't replied earlier.
 
  • #9
Hi Pavol Namer !
I used the formula with denominator at power 2. In fact, there is a typo on the figure attached to my answer : I forgot to write the power. It doesn't matter since it was only a skeched graph.
 

1. What is integral curve fitting in Origin?

Integral curve fitting in Origin is a data analysis technique used to fit a mathematical curve to experimental data points. It involves finding the best-fit parameters of a mathematical function that can be integrated to fit the data. This technique is commonly used in physics, chemistry, and other scientific fields to analyze and model complex data sets.

2. How does integral curve fitting work?

The integral curve fitting process involves selecting a mathematical function that best describes the experimental data and then finding the best-fit parameters for this function using optimization algorithms. The fitting process involves minimizing the sum of the squared differences between the experimental data points and the function's values at those points. This process is repeated until the best-fit curve is obtained.

3. What are the advantages of using integral curve fitting in Origin?

One of the main advantages of using integral curve fitting in Origin is its ability to handle complex data sets and find the best-fit curve that accurately represents the data. This technique also allows for the estimation of uncertainties in the fitted parameters, which can provide valuable insights into the reliability of the fitted curve. Additionally, Origin software provides a user-friendly interface and a wide range of tools for data visualization and analysis.

4. What types of functions can be used for integral curve fitting in Origin?

Origin software offers a variety of built-in mathematical functions that can be used for integral curve fitting, such as polynomial, exponential, logarithmic, and power functions. Users can also define their own custom functions or import functions from external sources to fit their data.

5. Can integral curve fitting be used for non-linear data?

Yes, integral curve fitting in Origin can be used for both linear and non-linear data. This technique is particularly useful for non-linear data, as it can handle complex relationships between variables and provide a more accurate fitting compared to linear regression methods.

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