Description Details Author(s) References See Also Examples
The main purpose of this package is to allow non-linear fitting within a GAMLSS model.
The main function nlgamlss()
can fit any parametric
(up to four distribution parameters) GAMLSS family of distributions.
Package: | gamlss-nl |
Type: | Package |
Version: | 1.5.0 |
Date: | 2005-12-12 |
License: | GPL (version 2 or later) |
Mikis Stasinopoulos <d.stasinopoulos@londonmet.ac.uk>, Bob Rigby <r.rigby@londonmet.ac.uk> based on work of Jim Lindsey and Philippe Lambert.
Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape, (with discussion), Appl. Statist., 54, part 3, pp 507-554.
Stasinopoulos D. M., Rigby R.A. and Akantziliotou C. (2003) Instructions on how to use the GAMLSS package in R. Accompanying documentation in the current GAMLSS help files, (see also http://www.gamlss.com/).
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Loading required package: gamlss
Loading required package: splines
Loading required package: gamlss.data
Attaching package: 'gamlss.data'
The following object is masked from 'package:datasets':
sleep
Loading required package: gamlss.dist
Loading required package: MASS
Loading required package: nlme
Loading required package: parallel
********** GAMLSS Version 5.1-3 **********
For more on GAMLSS look at http://www.gamlss.org/
Type gamlssNews() to see new features/changes/bug fixes.
Loading required package: survival
Warning messages:
1: In sqrt(diag(cov)) : NaNs produced
2: In sqrt(1/diag(V)) : NaNs produced
3: In cov2cor(cov) :
diag(.) had 0 or NA entries; non-finite result is doubtful
******************************************************************
Summary of the Quantile Residuals
mean = 0.05744272
variance = 1.01691
coef. of skewness = -0.02002806
coef. of kurtosis = 2.768721
Filliben correlation coefficient = 0.997461
******************************************************************
*******************************************************************
Family: c("JSU", "Johnson SU")
Call: nlgamlss(y = PET60, mu.fo = ~bflow * (1 - p1 * exp(-p2/bflow)),
sigma.formula = ~1, nu.fo = ~1, mu.start = c(0.6, 110), sigma.start = 3,
nu.start = 1, tau.start = 0.6, family = JSU, data = la)
Fitting method: "JL()"
-------------------------------------------------------------------
Mu link function: identity
Mu Coefficients:
Estimate Std. Error t-value p-value
p1 0.6192 0.01296 47.76 0.000e+00
p2 104.1209 8.14579 12.78 2.062e-37
-------------------------------------------------------------------
Sigma link function: log
Migma Coefficients:
Estimate Std. Error t-value p-value
(Intercept) 3.105 0.05344 58.1 0
-------------------------------------------------------------------
Nu link function: identity
Nu Coefficients:
Estimate Std. Error t-value p-value
(Intercept) 305.7 NaN NaN NaN
-------------------------------------------------------------------
Tau link function: log
Tau Coefficients:
Estimate Std. Error t-value p-value
(Intercept) 1.271 0.2054 6.186 6.169e-10
-------------------------------------------------------------------
No. of observations in the fit: 251
Degrees of Freedom for the fit: 5
Residual Deg. of Freedom: 246
at cycle: 48
Global Deviance: 2253.45
AIC: 2263.45
SBC: 2281.077
*******************************************************************
[,1] [,2] [,3] [,4] [,5]
[1,] 1.680787e-04 0.08226641 5.054987e-05 -2.953835e-01 0.000603431
[2,] 8.226641e-02 66.35381863 1.312628e-01 -2.264095e+02 0.360611453
[3,] 5.054987e-05 0.13126282 2.855724e-03 -5.413819e-01 -0.005067525
[4,] -2.953835e-01 -226.40946128 -5.413819e-01 -4.426809e+10 -0.993694188
[5,] 6.034310e-04 0.36061145 -5.067525e-03 -9.936946e-01 0.042204125
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