summaryGspline1 {glmmAK} | R Documentation

## Summary for a univariate G-spline (penalized Gaussian mixture)

### Description

This function is primarily designed to work out the MCMC output from functions `cumlogitRE` and `logpoissonRE` in which a distribution of the univariate random effect was specified as a G-spline. It computes posterior pointwise mean and quantiles for a G-spline density based on the MCMC output.

### Usage

    summaryGspline1(x, mu, sigma,
       standard=TRUE, intcpt, scale,
       probs, values=FALSE,
       dir=getwd(), wfile="logweight.sim", header=TRUE, logw=TRUE,
       skip=0, nwrite)

### Arguments

`x` | grid of values at which we want to evaluate the G-spline density
`mu` | a vector with G-spline knots (means of basis G-splines)
`sigma` | basis standard deviation(s). If a single number is supplied then it is assumed that all basis G-splines have the same standard deviation. Alternatively a vector of the same length as `mu` can be given in which case the basis G-splines do not necessarily have the same standard deviations
`standard` | logical, if `TRUE` then the standardized (zero-mean, unit-variance) G-spline densities are computed and summarized
`intcpt` | a vector with sampled intercept values. If not supplied it is assumed that all intercepts are equal to zero. It does not have to be supplied if `standard=TRUE`.
`scale` | a vector with sampled values of the G-spline scale (in most of my papers denoted by tau) If not supplied it is assumed that all scale values are equal to one. It does not have to be supplied if `standard=TRUE`.
`probs` | probabilities for which the (pointwise) sample quantiles of the G-spline density should be computed. If not given only average (and values) of the G-spline are computed
`values` | if `TRUE` also values of the G-spline at each (MCMC) iteration are returned. If `FALSE` only sample mean (and quantiles) of the G-spline are returned
`dir` | character giving the directory where the file with (sampled) G-spline (log-)weights is stored
`wfile` | character giving the name of the file with (sampled) G-spline (log-)weights
`header` | logical indicating whether the file `wfile` contains a header
`logw` | logical indicating whether the file `wfile` contains logarithms of the weights
`skip` | number of data rows that should be skipped at the beginning of the file `wfile`
`nwrite` | frequency with which is the user informed about the progress of computation (every `nwrite`th iteration count of iterations change)

### Value

A list with the following components (component values is present only when the argument `values` was `TRUE`):

`summary` | a `data.frame` with the following columns (the description below applies to the situation when `probs=0.5`):
x | a grid of values at which the G-spline density is evaluated
Mean | pointwise posterior mean of the G-spline density
50% | pointwise posterior 50% quantile of the G-spline density.
| There is one column of this type for each `probs` value
`values` | a matrix with one column for each `x` value and number of rows equal to the length of the MCMC. In each row, there is a G-spline density evaluated at one MCMC iteration.

### Author(s)

Arnošt Komárek arnost.komarek[AT]mff.cuni.cz

### Examples

    ### See ex-Toenail.pdf, ex-Toenail.R
    ### and ex-Epileptic.pdf, ex-Epileptic.R
    ### available in the documentation
    ### to the package

[Package glmmAK version 1.3-1 Index]