This is support for the smoother function nn() an interface for Brian Reply's nnet() function. It is not intended to be called directly by users.
● Data Source:
CranContrib
● Keywords: regression
● Alias: gamlss.nn
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plot.nnet
(Package: gamlss.add) :
Plotting fitted neural networks
A function to plot the results of a neural network fit based on the plotnet() function of the package NeuralNetTools
● Data Source:
CranContrib
● Keywords: regression
● Alias: plot.nnet
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fk
(Package: gamlss.add) :
A function to fit break points within GAMLSS
The fk() function is a additive function to be used for GAMLSS models. It is an interface for the fitFreeKnots() function of package gamlss.util. The functions fitFreeKnots() was first based on the curfit.free.knot() function of package DierckxSpline of Sundar Dorai-Raj and Spencer Graves. The function fk() allows the user to use the free knots function fitFreeKnots() within gamlss. The great advantage of course comes from the fact GAMLSS models provide a variety of distributions and diagnostics.
● Data Source:
CranContrib
● Keywords: regression
● Alias: fk, fk.control
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The function blag() creates a basis for lag values of x, (a matrix of lag values of x). The function llag() creates a list with two components i) a basis matrix and ii) weights to be used as prior weights in any regression analysis. The function wlag() can take a "mlags" object (created by blag()) or a vector and returns a vector with ones and zeros. This can be used as prior weights in any analysis which uses blag().
● Data Source:
CranContrib
● Keywords: regression, ts
● Alias: blag, llag, wlag
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This is support for the smoother function ga() an inteface for Simon Woood's gam() function. It is not intended to be called directly by users.
● Data Source:
CranContrib
● Keywords: regression
● Alias: gamlss.ga
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The function la() can be used for fitting penalised lags for explanatory variables.
● Data Source:
CranContrib
● Keywords: regression, ts
● Alias: gamlss.la, la, la.control
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This is support for the functions fk(). It is not intended to be called directly by users. T he function gamlss.fk is calling on the R function curfit.free.knot() of Sundar Dorai-Raj
● Data Source:
CranContrib
● Keywords: regression
● Alias: gamlss.fk
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ga
(Package: gamlss.add) :
A interface function to use Simon Wood's gam() function within GAMLSS
The ga() function is a additive function to be used within GAMLSS models. It is an interface for the gam() function of package mgcv of Simon Wood. The function ga() allows the user to use all the available smoothers of gam() within gamlss. The great advantage of course come from fitting models outside the exponential family.
● Data Source:
CranContrib
● Keywords: regression
● Alias: ga, ga.control
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fitFixedKnots
(Package: gamlss.add) :
Functions to Fit Univariate Break Point Regression Models
There are two main functions here. The functions fitFixedKnots allows the fit a univariate regression using piecewise polynomials with "known" break points while the function fitFreeKnots estimates the break points.
● Data Source:
CranContrib
● Keywords: regression
● Alias: fitFixedKnots, fitFreeKnots
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nn
(Package: gamlss.add) :
A interface function to use nnet() function within GAMLSS
The nn() function is a additive function to be used for GAMLSS models. It is an interface for the nnet() function of package nnet of Brian Ripley. The function nn() allows the user to use neural networks within gamlss. The great advantage of course comes from the fact GAMLSS models provide a variety of distributions and diagnostics.
● Data Source:
CranContrib
● Keywords: regression
● Alias: nn, nn.control
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