[R] nls and "plinear" algorithm
Allan Clark
Allan.Clark at uct.ac.za
Tue Jul 8 20:33:40 CEST 2008
hello all
i havnt had a chance to read through the references provided for the
"nls" function (since the libraries are closed now).
can anyone shed some light on how the "plinear" algorithm works? also,
how are the fitted values obtained? also, WHAT DOES THE ".lin" below
REPRESENT?
thanking you in advance
######################################
i have a quick example: (data below)
f1=nls(r~242*(p+exp(-a1*p)/a1-1/a1)*(1-exp(-a2*o))/(
(100+exp(-a1*100)/a1-1/a1)*(1-exp(-a2*50)) ) , data = X.m,
algorithm="plinear",start = list(a1=0.01,a2=.01),trace = TRUE)
> summary(f1)
Formula: r ~ 242 * (p + exp(-a1 * p)/a1 - 1/a1) * (1 - exp(-a2 *
o))/((100 +
exp(-a1 * 100)/a1 - 1/a1) * (1 - exp(-a2 * 50)))
Parameters:
Estimate Std. Error t value Pr(>|t|)
a1 0.027017 0.003493 7.735 6.34e-10 ***
a2 0.154967 0.012214 12.688 < 2e-16 ***
.lin 1.042452 0.008010 130.140 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 3.979 on 47 degrees of freedom
Number of iterations to convergence: 13
Achieved convergence tolerance: 8.91e-06
p r o
98.96338287 241.2828283 50
97.55260431 237.6262626 49
95.63989983 233.0606061 48
93.91802748 229.3232323 47
92.31404009 224.7575758 46
90.03746768 220.7878788 45
89.30649329 216.6868687 44
87.64125166 212.2020202 43
86.68123643 207.4646465 42
85.25030371 203.3939394 41
83.64465743 198.5252525 40
82.60251377 193.8787879 39
81.62361512 189.1717172 38
80.71350574 185.1111111 37
79.15697699 180.7171717 36
78.11234178 176.5858586 35
76.60248492 172.7272727 34
76.03845076 168.5353535 33
74.32556341 164.6060606 32
73.3639895 160.3939394 31
72.35840786 156.7272727 30
70.90629218 152.5454545 29
69.88235864 148.6161616 28
68.69538137 144.1818182 27
67.6875564 140.5151515 26
67.16355934 135.7373737 25
66.90502437 131.3636364 24
65.63480302 126.8484848 23
64.63355769 122.1111111 22
63.5529748 117.4040404 21
62.65320004 113.4444444 20
61.31100803 109.0505051 19
60.59542007 105.1836735 18
58.43200533 100.244898 17
57.13903832 96.68041237 16
56.46953877 92.45833333 15
54.79475954 87.52083333 14
53.85049475 82.21875 13
52.50164551 77.84210526 12
51.04072849 72.87234043 11
49.64840803 68.22580645 10
48.24666285 62.76344086 9
46.36813455 58.0989011 8
44.40690015 51.85714286 7
42.8855932 45.13333333 6
40.93434063 39.34090909 5
37.84871552 32.39772727 4
36.10687426 25.8372093 3
32.74320593 18.26829268 2
28.03072554 9.922077922 1
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