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Differences between version dated 2004-06-03 16:46:35 and 2004-11-20 20:47:59 (spanning 17 versions)
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ȸ±ÍºÐ¼®À» ÅëÇÑ ÅͳΠºØ±«µµ ¹× ÇÔ¼ö Ãß»ê ÇÁ·ÎÁ§Æ®.

ȸ±ÍºÐ¼®À» ÅëÇÑ ÅͳΠºØ±«µµ(³»°øº¯À§)¿¡ ´ëÇÑ ÇÔ¼ö ¸ðµ¨¸µ ÇÁ·ÎÁ§Æ®.

 

 * ±â°£ ; 2004-05-26 ~ 2004-06-23(¼ö, ¿¹Á¤)

 * »ç¾÷¸í ; ÅͳΰèÃø°ü¸® Manual Ç¥ÁØÈ­ ((ÁÖ)Æ÷½ºÄڰǼ³ - ÀÎÇÏ´ë)

 * ±â°£ ; 2004-05-26 ~ 2004-06-23(¼ö, ¿¹Á¤), 7¿ù 3ÀÏ°æ Á¾·á.

 
 * °áÁ¤»çÇ×
  * ´ÜÀÏ ¾îÇø®ÄÉÀ̼Ç, c++ based(maybe)

  Cx(1+m) : ±¼Âø¸éÀÌ ¹«ÇÑÈ÷ ¸Ö°í Àå½Ã°£ÀÌ °æ°úÇÑ ÈÄÀÇ ÃÖÁ¾ ³»°øº¯À§
  (õÃþ_±¤ÆøÅͳÎÀÇ_³»°øº¯À§_¹×... ¿¡¼­ ¹ßÃé)
 

==== ¿ÀÀü 3:08 2004-06-14, by Kenial ====

Upload:sample.zip »ùÇà µ¥ÀÌÅÍ

Upload:20040613_r_script.txt nls ½ºÅ©¸³Æ®

 

==== ¿ÀÈÄ 9:55 2004-06-11, by Kenial ====

ÆĶó¸ÞÅÍ ¹üÀ§(¿¹»ó)

 * refA : 'õÃþ_±¤ÆøÅͳÎÀÇ_³»°øº¯À§_¹×_ħÇϰŵ¿Æ¯¼º_¿¹ÃøÀ»_À§ÇÑ_¼öÄ¡Çؼ®Àû_¿¬±¸.pdf'

 * refB : 'ÅͳÎ_³»°øº¯À§ÀÇ_À̷аú_°èÃø°á°úÀÇ_ºÐ¼®.pdf'

 

 1 .1. C(x) : refA, p.25

  * 3.05 <= a <= 7.55

  * .035 <= b <= .058

  * .13 <= c0 <= 2.43

 

 1 .2a. C(t) : refA, p.25

  * 3.08 <= a <= 7.08

  * .01 <= b <= .03

  * -.002 <= c0 <= 1.24

 

 1 .2b. C(t) : refB, p.86

  * 4.94 <= a <= 16.76

  * .11 <= b <= .52

  * -1.34 <= c0 <= 8.18

  * 2.1 <= S(%) <= 31.2

 

 2 . Ãß»êÇÒ °Í..

 

 3 . C(x) : refA, p.25

  * 3.59 <= Cx <= 9.1

  * 24.9 <= X <= 46.9

  * 0.39 <= c0 <= 3.46

 

 4 . C(x,t) : 1.1, 1.2a, 1.2b ·ÎºÎÅÍ Ãß»ê = {1.1}, ({1.2a} + {1.2b}) / 2

  * 3.05 <= a <= 7.55

  * .035 <= b <= .058

  * 4.01 <= c <= 11.92

  * .06 <= d <= .28

  * -.61 <= c0 <= 3.57

 

 5 . C(x,t) : refB : p.88

  * 9.4 <= Cx <= 14.5

  * 3.5 <= X <= 7.3

  * .15 <= T <= 1.15

  * 3.8 <= m <= 7.1

  * 14.4 <= C0 <= 32

  * 12 <= C0/Ctot(%) <= 21

  * 46.5 <= Ctot <= 99.1

  * 2.1 <= S(%) <= 5.4

 

==== ¿ÀÀü 12:55 2004-06-10, by Kenial ====

Å×½ºÆ®¿ë ÆĶó¸ÞÅÍ

{{{

1-1

  C0 .107785647

  A 1.305090740

  B .074960389

1-2

  C0 .191568085

  A 1.412937532

  B .094437384

2(ÀÌ°Ç Á» ³ªÁß¿¡)

  C0 2.255114380

  A .259494577

  B 8646.0555381

3

  C0 .167183448

  CX 1.393850202

  XX 19.733595112

4

  C0 -1.580096488

  A 1.471346848

  B .088694718

  C -1.858608651

  D 2.493052423

5

  C0 .430609326

  CX 3.93449954

  XX 8.83168773

  T 2.25797694

  M -.58709922

}}}

==== ¿ÀÀü 10:51 2004-06-08, by Kenial ====

°ÅÀÇ ¸¶Âù°¡Áö °á·ÐÀÌÁö¸¸, r-project¿¡¼­µµ ¸ð¼ö¸¦ ÀûÀýÈ÷ Á¶ÀýÇÏ¸é °°Àº(!) °á°ú¸¦ ¾òÀ» ¼ö ÀÖÀ½.

´ë½Å, ¸ð¼öÀÇ °ª¿¡ ÀÌ»óÀÌ ÀÖÀ» ¶§ ±× ÇØ°áÁ¡À» ã´Â ¹üÀ§¿¡¼­ spss°¡ Á» ´õ ¿ì¼ö.

 

try to do : r-project¿¡¼­ ¸ð¼öÀÇ °ªÀÇ ¹üÀ§¸¦ Á¤ÇÑ ´ÙÀ½ °¢°¢ÀÇ °ª¿¡ ´ëÇÑ divide-and-conquer ½Ãµµ.

  °³°³ÀÇ °ªÀº ¸ð¼ö°¡ °¡Áú ¼ö ÀÖ´Â ÃÖ¼Ò/ÃÖ´ë°ªÀ» 10µîºÐÇÑ °ªÀ¸·Î Çϸç, 10ȸÀÇ ½Ãµµ¿¡ ½ÇÆÐÇϸé

  °³°³ÀÇ ¸ð¼ö¸¶´Ù 10´Ü°èÀÇ °ªÀ» ÃëÇØ ¸ð¼ö ÇϳªÇϳªÀÇ °ªÀ» º¯°æÇØ°¡¸ç divide-and-conquer ½Ãµµ

  (ÃÖ¾ÇÀÇ °æ¿ì 10^p ¹øÀÇ ½Ãµµ : p=¸ð¼öÀÇ °³¼ö)

 

==== ¿ÀÀü 1:22 2004-06-08, by Kenial ====

¸ð¼öparameter Á¶Á¤ ¼º°ø!

Upload:spsssyntax_parametered.txt

 

´ë·« ¾î¹ö¹öÇÏÁö¸¸ À¢°£ÇÑ °á°úÄ¡¿¡¼­´Â 4°³ ÀÌ»óÀÇ ¹æÁ¤½ÄÀÌ 80% ÀÌ»óÀÇ r^2 °ªÀ» º¸ÀÓ.

 

==== ¿ÀÀü 1:03 2004-06-07, by Kenial ====

r-project¿¡¼­ÀÇ nonlinear regression ÇÔ¼ö Å×½ºÆ® Áß.

 

tunnel <- read.table("d:tunnel.txt", TRUE)

ft1 <- nls( c ~ A * ( 1 - exp( -B * x ) ) - c0, data = tunnel,

 algorithm = "plinear",

 start = list( A=0, B=0, c0=0 ), trace = TRUE)

 

ft1 <- nls( c ~ (( 1 - exp( -B * x ) ) * A ) - c0, data = tunnel,

 start = list(A=0, B=0, c0=0 ), trace = TRUE)

 

ft1 <- nls( c ~ (( 1 - exp( -B * t ) ) * A ) - c0, data = tunnel,

 start = list(A=0, B=0, c0=0 ), trace = TRUE)

 

ft1 <- nls( c ~ ( A * log(1 + (B*t)) ) - c0, data = tunnel,

 start = list(A=0, B=0, c0=0 ), trace = TRUE)

 

ft1 <- nls( c ~ ( 1 - ( ( XX / ( XX + x ) ) ** 2 ) ) - c0, data = tunnel,

 start = list(XX=0, c0=0 ), trace = TRUE)

 

ft1 <- nls( c ~ pa * (1 - exp(-pb * x)) + pc * (1 - exp(-pd * t)) - c0, data = tunnel,

 start = list(pa=0, pb=0, pc=0, pd=0, c0=0 ), trace = TRUE)

 

ft1 <- nls( c ~ PCX*(1- ( (PX/(PX+x)) **2 )) * (1+ PM*(1-((PT/(PT+t))**0.3))) - c0,

 data = tunnel, start = list(PCX=0, PX=0, PM=0, PT=0, c0=0 ), trace = TRUE)

 

----

°á±¹ ¶Ç »ðÁú ÀÛ¾÷À» ÇßÀ½ÀÌ ¹àÇôÁü.

±âÃÊ parameter 0À¸·Î Á¶Á¤ ¾øÀÌ

3¹ø ¸ðµ¨¿¡¼­ R^2 = .98826, 5¹ø ¸ðµ¨¿¡¼­ R^2 = .91620 ¼öÄ¡ ³ª¿È

(5¹ø ¸ðµ¨ÀÇ °æ¿ì Ç¥ÁØ¿ÀÂ÷°¡ »ó´çÇÏ¿© º° Àǹ̰¡ ¾ø´Â °ª)

 

³»°øº¯À§ÀÇ °ªÀº ÃøÁ¤Ä¡¿¡ -1À» °öÇØÁÖ¾î¾ß ÇßÀ½.

 

3¹ø ¸ðµ¨ÀÇ °á°ú :

{{{

Nonlinear Regression Summary Statistics Dependent Variable C

 

  Source DF Sum of Squares Mean Square

 

  Regression 3 10.27649 3.42550

  Residual 10 .01351 1.350632E-03

  Uncorrected Total 13 10.29000

 

  (Corrected Total) 12 1.15077

 

  R squared = 1 - Residual SS / Corrected SS = .98826

 

                                           Asymptotic 95 %

                          Asymptotic Confidence Interval

  Parameter Estimate Std. Error Lower Upper

 

  C0 .129819687 .050150412 .018077605 .241561769

  CX 1.139746965 .049305817 1.029886758 1.249607172

  XX 15.949666320 1.886976217 11.745221299 20.154111341

}}}

 

stableÇÑ °ªÀº ¾Æ´ÏÁö¸¸, ÃʱâÄ¡ÀÇ ¼³Á¤¿¡ µû¶ó Á¦´ë·Î µÈ °ªÀ» ¾ò¾î³¾ ¼ö ÀÖÀ» µí ÇÔ.

 

==== ¿ÀÀü 2:20 2004-06-06, by Kenial ====

* A * ( 1 - EXP(-B*x) ).

* NonLinear Regression.

MODEL PROGRAM c0=0 A=0 B=0 .

COMPUTE PRED_ = A * ( 1 - EXP(-B*x) ) - c0.

NLR c

  /OUTFILE='C:\SPSSFNLR.TMP'

  /PRED PRED_

  /CRITERIA SSCONVERGENCE 1E-8 PCON 1E-8 .

 

* A * ( 1 - EXP(-B*t) ).

* NonLinear Regression.

MODEL PROGRAM c0=0 A=0 B=0 .

COMPUTE PRED_ = A * ( 1 - EXP(-B*t) ) - c0.

NLR c

  /OUTFILE='C:\SPSSFNLR.TMP'

  /PRED PRED_

  /CRITERIA SSCONVERGENCE 1E-8 PCON 1E-8 .

 

* A * ln(1 + (B*t))

* NonLinear Regression.

MODEL PROGRAM c0=0 A=0 B=0 .

COMPUTE PRED_ = A * ln(1 + (B*t)) - c0.

NLR c

  /OUTFILE='C:\SPSSFNLR.TMP'

  /PRED PRED_

  /CRITERIA SSCONVERGENCE 1E-8 PCON 1E-8 .

 

* Cx * ( 1 - ( ( XX / ( XX + x ) ) ** 2 ) ).

* NonLinear Regression.

MODEL PROGRAM c0=0 Cx=-1.20 XX=0 .

COMPUTE PRED_ = Cx * ( 1 - ( ( XX / ( XX + x ) ) ** 2 ) ) - c0.

NLR c

  /OUTFILE='C:\SPSSFNLR.TMP'

  /PRED PRED_

  /CRITERIA SSCONVERGENCE 1E-8 PCON 1E-8 .

 

* pa * (1-EXP(-pb * x)) + pc * (1-EXP(-pd * t)).

* NonLinear Regression.

MODEL PROGRAM c0=0 PA=0 PB=0 PC=0 PD=0 .

COMPUTE PRED_ = pa * (1-EXP(-pb * x)) + pc * (1-EXP(-pd * t)) - c0.

NLR c

  /OUTFILE='C:\SPSSFNLR.TMP'

  /PRED PRED_

  /CRITERIA SSCONVERGENCE 1E-8 PCON 1E-8 .

 

* PCX * ( 1 - ( ( PX / ( PX + x ) ) **2 ) ) * ( 1 + PM * ( 1- (( PT / (PT + t ) ) **0.3 ) )).

* NonLinear Regression.

MODEL PROGRAM c0=0 PCX=0 PX=0 PT=0 PM=0 .

COMPUTE PRED_ = PCX * ( 1 - ( ( PX / ( PX + x ) ) **2 ) ) * ( 1 + PM * ( 1- (( PT / (PT + t ) ) **0.3 ) )) - c0.

NLR c

  /OUTFILE='C:\SPSSFNLR.TMP'

  /PRED PRED_

  /CRITERIA SSCONVERGENCE 1E-8 PCON 1E-8 .

 

==== ¿ÀÀü 1:42 2004-06-04, by Kenial ====

¹º°¡ µÇ´Â °Í °°±âµµ ÇÏ°í ¾Æ´Ñ °Í °°±âµµ ÇÏ°í.. ȯÀåÇÏ°Ú³×.~

Cm = C(x,t) - C0 ... ¾Æ Á¨Àå ¼ö½Äµµ Á¦´ë·Î üũ¸¦ ¾ÈÇÏ°í »¹ÁþÇÏ´Ù´Ï ...

 

Levenberg-Marquardt MethodÀÌ ¾Æ´Ï¶ó¸é... sequential quadratic programmingÀÌ´Ù!

 

==== ¿ÀÈÄ 4:18 2004-06-03, by Kenial ====
 Levenberg-Marquardt Method¿¡ ´ëÇؼ­...
http://groups.google.co.kr/groups?hl=ko&lr=&ie=UTF-8&newwindow=1&threadm=8kjf16%24mnf%241%40b5nntp2.channeli.net&rnum=3&prev=/groups%3Fq%3Dlevenverg-marquardt%2520algorithm%26hl%3Dko%26lr%3D%26ie%3DUTF-8%26newwindow%3D1%26sa%3DN%26tab%3Dwg

 * °³¹ß ¸ðµâ ºÐ¸®
  ; ÀÔ·Â µ¥ÀÌÅÍ Æļ­, ¼ö½Ä µ¥ÀÌÅÍ ÀúÀå/Equatation Ãâ·Â/Graph Ãâ·Â Ŭ·¡½º, Regression ÇÁ·Î¼¼½Ì ¸ðµâ
----

[±âŸºÐ·ù]

[±âŸºÐ·ù] [WorkBook]


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