[R] profile error on an nls object
Adrian Dragulescu
adrian_d at eskimo.com
Thu Mar 18 23:49:37 CET 2004
Hello all,
This is the error message that I get.
> hyp.res <- nls(log(y)~log(pdf.hyperb(theta,X)), data=dataModel,
+ start=list(theta=thetaE0),
+ trace=TRUE)
45.54325 : 0.1000000 1.3862944 -4.5577142 0.0005503
3.728302 : 0.0583857346 0.4757772859 -4.9156128701 0.0005563154
1.584317 : 0.0194149477 0.3444648833 -4.9365149150 0.0004105426
1.569333 : 0.0139310639 0.3824648048 -4.9024001228 0.0004089738
1.569311 : 0.0137155342 0.3888648619 -4.8979817546 0.0004137501
1.569311 : 0.0136895846 0.3893564152 -4.8976182201 0.0004141057
1.569311 : 0.0136876315 0.3894059947 -4.8975821760 0.0004141343
> hyp.res.S <- summary(hyp.res)
> hyp.res.S
Formula: log(y) ~ log(pdf.hyperb(theta, X))
Parameters:
Estimate Std. Error t value Pr(>|t|)
theta1 0.0136876 0.0359964 0.380 0.705
theta2 0.3894060 0.3079860 1.264 0.211
theta3 -4.8975822 0.2219928 -22.062 <2e-16 ***
theta4 0.0004141 0.0005457 0.759 0.451
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
Residual standard error: 0.1542 on 66 degrees of freedom
Correlation of Parameter Estimates:
theta1 theta2 theta3
theta2 -0.02168
theta3 -0.02029 0.997736
theta4 -0.97182 -0.008054 -0.008952
> pr1 <- profile(hyp.res)
1.825584 : 0.3894059947 -4.8975821760 0.0004141343
1.58426 : 0.373691474 -4.909091289 0.000824045
1.583673 : 0.4176596873 -4.8774106487 0.0008176545
1.583670 : 0.4196944963 -4.8760375504 0.0008187918
1.583670 : 0.4199010211 -4.8758854269 0.0008188162
1.624899 : 0.449756713 -4.854643555 0.001215014
1.624743 : 0.46804752 -4.84185838 0.00122343
1.624741 : 0.470384534 -4.840195293 0.001224199
1.624741 : 0.470638282 -4.840013199 0.001224298
1.624741 : 0.470670500 -4.839990112 0.001224309
1.692158 : 0.522188258 -4.803565745 0.001635778
1.691853 : 0.540794581 -4.791027785 0.001650730
1.691847 : 0.544973564 -4.788090229 0.001652321
1.691847 : 0.545500818 -4.787718964 0.001652616
1.691847 : 0.545592388 -4.787654441 0.001652658
1.784749 : 0.622277872 -4.734086833 0.002091090
1.784039 : 0.642139831 -4.721442413 0.002115555
1.784022 : 0.649929188 -4.716068239 0.002119126
1.784021 : 0.651094995 -4.715267692 0.002119963
1.784021 : 0.65136956 -4.71507850 0.00212012
1.784021 : 0.651420684 -4.715043256 0.002120153
1.901667 : 0.760981513 -4.639871097 0.002604136
1.899765 : 0.782870773 -4.627113544 0.002644289
1.899703 : 0.798044378 -4.616913842 0.002653139
1.899699 : 0.800930030 -4.614996517 0.002655646
1.899699 : 0.801815115 -4.614404602 0.002656286
1.899699 : 0.802033012 -4.614258879 0.002656455
1.899699 : 0.802090888 -4.614220164 0.002656499
2.042311 : 0.960722487 -4.508069592 0.003221186
2.036028 : 0.985442669 -4.495703574 0.003291724
2.035767 : 1.017849320 -4.474692317 0.003317203
2.035736 : 1.026482531 -4.469203277 0.003326355
2.035733 : 1.029937702 -4.466987738 0.003329627
2.035732 : 1.031114541 -4.466233213 0.003330776
2.035732 : 1.03153247 -4.46596514 0.00333118
2.035732 : 1.031679019 -4.465871141 0.003331322
2.035732 : 1.031730150 -4.465838341 0.003331371
1.583425 : 3.595503e-01 -4.918824e+00 1.793668e-05
1.583270 : 3.783622e-01 -4.905413e+00 2.175254e-05
1.58327 : 3.793739e-01 -4.904683e+00 2.134353e-05
1.58327 : 3.794562e-01 -4.904622e+00 2.133204e-05
1.624847 : 0.3695765499 -4.9116128267 -0.0003687005
1.624748 : 0.3877816645 -4.8985581022 -0.0003699797
1.624747 : 0.3890277914 -4.8976645481 -0.0003706884
1.624747 : 0.3891837724 -4.8975508910 -0.0003707385
1.693266 : 0.3989123147 -4.8904787597 -0.0007628478
1.693170 : 0.4172349434 -4.8774484377 -0.0007692982
1.693168 : 0.4193992605 -4.8759045536 -0.0007705839
1.693168 : 0.4197576966 -4.8756463144 -0.0007707548
1.693168 : 0.4198094076 -4.8756090629 -0.0007707816
1.788041 : 0.450653198 -4.853510937 -0.001173674
1.787884 : 0.469850125 -4.840178495 -0.001186483
1.787878 : 0.473941725 -4.837285088 -0.001188994
1.787878 : 0.474783800 -4.836687703 -0.001189518
1.787878 : 0.474960093 -4.836562526 -0.001189627
1.787878 : 0.474996400 -4.836536741 -0.001189650
1.908362 : 0.531011661 -4.796878005 -0.001614805
1.907987 : 0.552282889 -4.782714884 -0.001637055
1.907965 : 0.560264832 -4.777154923 -0.001642437
1.907964 : 0.562346209 -4.775709348 -0.001644026
1.907963 : 0.56295255 -4.77528733 -0.00164447
1.907963 : 0.563123513 -4.775168321 -0.001644596
1.907963 : 0.563172014 -4.775134556 -0.001644632
2.053048 : 0.653571857 -4.712183501 -0.002111091
2.051874 : 0.678913471 -4.696423681 -0.002150202
2.051785 : 0.69544095 -4.68518302 -0.00216328
2.051772 : 0.701166962 -4.681323343 -0.002168564
2.051770 : 0.703471045 -4.679765756 -0.002170603
2.051769 : 0.704360670 -4.679164327 -0.002171397
2.051769 : 0.704707691 -4.678929683 -0.002171706
2.051769 : 0.704842651 -4.678838422 -0.002171826
2.051769 : 0.704895042 -4.678802995 -0.002171872
3.874239 : 0.0136876315 -4.8975821760 0.0004141343
1.683633 : 0.0140300885 -5.1010837614 0.0004228894
1.582383 : 0.0159635264 -5.0698805881 0.0003921865
1.582380 : 0.0156612906 -5.0699927701 0.0003961255
1.582380 : 0.0156714529 -5.0699887428 0.0003959888
1.62839 : 0.0177072933 -5.2469160871 0.0003773674
1.62302 : 0.0173703508 -5.2549785000 0.0003824169
1.623010 : 0.017454006 -5.254634273 0.000381311
1.623010 : 0.017450834 -5.254646856 0.000381349
1.693919 : 0.0192287068 -5.4391483575 0.0003667216
1.688721 : 0.0188383089 -5.4474923226 0.0003715871
1.688708 : 0.0189024936 -5.4470793675 0.0003708466
1.688708 : 0.0189011857 -5.4470970845 0.0003708537
1.781934 : 0.0203962009 -5.6454738631 0.0003600353
1.776866 : 0.0199673656 -5.6541185083 0.0003646648
1.776849 : 0.0200118977 -5.6536319416 0.0003642738
1.776849 : 0.0200100558 -5.6536559449 0.0003642825
1.889638 : 0.0211923804 -5.8738978163 0.0003572760
1.884404 : 0.0207378220 -5.8830916118 0.0003616144
1.884382 : 0.020765806 -5.882510312 0.000361524
1.884382 : 0.0207622023 -5.8825427275 0.0003615496
1.884382 : 0.0207620572 -5.8825409040 0.0003615529
2.013048 : 0.0215963002 -6.1364575433 0.0003585248
2.007339 : 0.0211300497 -6.1464738264 0.0003624619
2.00731 : 0.0211456623 -6.1457695801 0.0003626177
2.00731 : 0.0211391005 -6.1458133458 0.0003626743
2.00731 : 0.0211385176 -6.1458106028 0.0003626839
1.588746 : 0.0116517911 -4.7206548317 0.0004327556
1.58227 : 0.0113562764 -4.7282291715 0.0004385397
1.582266 : 0.0114927727 -4.7280477868 0.0004363126
1.582266 : 0.0114778523 -4.7280512493 0.0004365554
1.626601 : 0.0092002102 -4.5533139799 0.0004596651
1.619645 : 0.0089799845 -4.5607704466 0.0004657534
1.619642 : 0.0091267199 -4.5606310820 0.0004631665
1.619642 : 0.0091061083 -4.5606330852 0.0004635248
1.686974 : 0.0065887359 -4.3829352072 0.0004921501
1.679178 : 0.006431904 -4.390438771 0.000499185
1.679176 : 0.0065909364 -4.3903319603 0.0004961289
1.679176 : 0.0065644067 -4.3903330820 0.0004966265
1.679176 : 0.0065683565 -4.3903330201 0.0004965523
1.767647 : 0.003788939 -4.203815551 0.000532725
1.758289 : 0.0036705739 -4.2116327081 0.0005421454
1.758287 : 0.0038516622 -4.2115484360 0.0005382965
1.758287 : 0.0038192070 -4.2115490856 0.0005389643
1.865816 : 0.0006957633 -4.0084238869 0.0005871507
1.853701 : 0.0005961484 -4.0168687626 0.0006016352
1.853699 : 0.0008362140 -4.0167968055 0.0005958852
1.853699 : 0.0007620456 -4.0167975560 0.0005975896
1.853699 : 0.0007701809 -4.0167974548 0.0005974007
1.978174 : -0.0028587603 -3.7850046811 0.0006669515
1.960889 : -0.0030688672 -3.7945046007 0.0006955498
1.960887 : -0.0027067062 -3.7944311799 0.0006854164
1.960887 : -0.0027920434 -3.7944320124 0.0006877001
5.64713 : 0.0136876315 0.3894059947 0.0004141343
1.629748 : 0.0155012039 0.1892390960 0.0003968719
1.581812 : 0.0156784380 0.1604443768 0.0003956682
1.581806 : 0.0155981707 0.1607541098 0.0003966080
1.581806 : 0.0156011476 0.1607440033 0.0003965726
1.625034 : 0.0176093652 -0.0792346636 0.0003781418
1.619729 : 0.0172570301 -0.0690409623 0.0003829002
1.619717 : 0.0172925225 -0.0695061842 0.0003825291
1.619717 : 0.0172912517 -0.0694884984 0.0003825385
1.685930 : 0.0190500552 -0.3090794855 0.0003679339
1.680988 : 0.0186534576 -0.2991696578 0.0003725206
1.680974 : 0.0186835862 -0.2996838489 0.0003722919
1.680974 : 0.0186818890 -0.2996610614 0.0003723024
1.768212 : 0.0201697584 -0.5459270795 0.0003613506
1.763496 : 0.0197433946 -0.5361742949 0.0003657251
1.763479 : 0.0197679071 -0.5367429015 0.0003656357
1.763479 : 0.0197650941 -0.5367140691 0.0003656558
1.869533 : 0.0209584525 -0.7978734727 0.0003583334
1.864765 : 0.0205126475 -0.7879935819 0.0003624617
1.864745 : 0.0205327327 -0.7886349546 0.0003624954
1.864745 : 0.0205286611 -0.7885983504 0.0003625264
1.864745 : 0.0205285176 -0.7886004594 0.0003625299
1.986651 : 0.0213989344 -1.0757885915 0.0003589658
1.981542 : 0.0209450354 -1.0654801197 0.0003627591
1.981515 : 0.0209633543 -1.0662185762 0.0003628857
1.981515 : 0.020956299 -1.066171806 0.000362947
1.981515 : 0.0209561876 -1.0661748041 0.0003629514
1.589875 : 0.0116794138 0.6293846615 0.0004325651
1.583420 : 0.0113555311 0.6404016532 0.0004381207
1.583415 : 0.0114133891 0.6400920083 0.0004372227
1.583415 : 0.0114079388 0.6400983595 0.0004373103
1.631556 : 0.0091559922 0.8877395583 0.0004602042
1.624037 : 0.0088957207 0.8995559273 0.0004663601
1.624033 : 0.0089630852 0.8992803329 0.0004651855
1.624033 : 0.008952827 0.899284613 0.000465364
1.697006 : 0.0064519740 1.1632996957 0.0004939404
1.688459 : 0.0062555272 1.1758143022 0.0005012813
1.688456 : 0.0063357705 1.1755760587 0.0004997134
1.688456 : 0.0063225169 1.1755787128 0.0004999653
1.783962 : 0.0035487681 1.4669400022 0.0005364535
1.773585 : 0.0033867882 1.4806292714 0.0005467553
1.773583 : 0.0034981174 1.4804153720 0.0005443142
1.773583 : 0.0034734893 1.4804170613 0.0005448297
1.889003 : 0.0003437136 1.8152947117 0.0005941152
1.875415 : 0.0002107001 1.8307953466 0.0006103544
1.875413 : 0.0002868541 1.8305923056 0.0006083076
1.875413 : 0.0003182105 1.8305924268 0.0006075744
1.875413 : 0.000300086 1.830592703 0.000608001
Error in prof$getProfile() : step factor 0.000488281 reduced below
`minFactor' of 0.000976563
>
Why is there an error on profile, which should only evaluate the
objective function for different parameter values?
Thanks a lot.
Adrian
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