lagPlot
(Package: gamlss.util) :
Lag plot for time series data
The function lagPlot() plots a time series variable against its lagged values or against the lagged values of an explanatory variable.
● Data Source:
CranContrib
● Keywords: ts
● Alias: lagPlot
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The function produced two dimensional smooth scatter plots. The method used is described in Eilers and Goeman (2004).
● Data Source:
CranContrib
● Keywords: regression
● Alias: scattersmooth
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penReg
(Package: gamlss.util) :
Function to fit penalised regression
The function penReg() can be used to fit a P-spline. It can be used as demonstration of how the penalised B-splines can be fitted to one explanatory variable. For more that one explanatory variables use the function pb() in gamlss. The function penRegQ() is similar to the function penReg() but it estimates the "random effect" sigmas using the Q-function (marginal likelihood). The Q-function estimation takes longer but it has the advantage that standard errors are provided for log σ_e and log σ_b, where the sigmas are the standard errors for the response and the random effects respectively. The function pbq() is a smoother within GAMLSS and should give identical results to the additive function pb(). The function gamlss.pbq is not for use.
● Data Source:
CranContrib
● Keywords: regression
● Alias: gamlss.pbq, pbq, penReg, penRegQ
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centiles.ts
(Package: gamlss.util) :
Plots the centile curves for a time series GAMLSS object
This function centiles.ts() plots centiles curves for time series response variables who's distributions belong to the GAMLSS family of distributions. The function also tabulates the sample percentages below each centile curve (for comparison with the model percentages given by the argument cent.)
● Data Source:
CranContrib
● Keywords: regression
● Alias: centiles.ts
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This function is for fitting a GARMA model, see Benjamin et al. (2003).
● Data Source:
CranContrib
● Keywords: models, regression
● Alias: garmaFit
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plotSimpleGamlss
(Package: gamlss.util) :
Plotting a simple GAMLSS model for demonstration purpose
This is to plot a simple GAMLSS model where only one explanatory variable exist in order to demonstrated how the distribution of the response changes according to values of the explanatory variable.
● Data Source:
CranContrib
● Keywords: regression
● Alias: plotSimpleGamlss
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