[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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