inspect_random | R Documentation |

Inspection and interpretation of random factor smooths.

inspect_random( model, select = 1, fun = NULL, cond = NULL, n.grid = 30, print.summary = getOption("itsadug_print"), plot = TRUE, add = FALSE, main = NULL, xlab = NULL, ylab = NULL, ylim = NULL, h0 = 0, v0 = NULL, eegAxis = FALSE, ... )

`model` |
A gam object, produced by |

`select` |
A number, indicating the model term to be selected. |

`fun` |
A string or function description to apply to the random effects estimates. When NULL (default), the estimates for the random effects are returned. |

`cond` |
A named list of the values to restrict the estimates for the random predictor terms. When NULL (default) all levels are returned. |

`n.grid` |
Number of data points estimated for each random smooth. |

`print.summary` |
Logical: whether or not to print a summary of the
values selected for each predictor.
Default set to the print info messages option
(see |

`plot` |
Logical: whether or not to plot the random effect estimates (TRUE by default). |

`add` |
Logical: whether or not to add the random effect estimates to an existing plot (FALSE by default). |

`main` |
Changing the main title for the plot, see also title. |

`xlab` |
Changing the label for the x axis, defaults to a description of x. |

`ylab` |
Changing the label for the y axis, defaults to a description of y. |

`ylim` |
Changing the y limits of the plot. |

`h0` |
A vector indicating where to add solid horizontal lines for reference. By default 0. |

`v0` |
A vector indicating where to add dotted vertical lines for reference. By default no values provided. |

`eegAxis` |
Whether or not to reverse the y-axis (plotting negative upwards). |

`...` |
other options to pass on to |

A data frame with estimates for random effects is optionally returned.

Jacolien van Rij

Other Functions for model inspection:
`dispersion()`

,
`fvisgam()`

,
`gamtabs()`

,
`plot_data()`

,
`plot_parametric()`

,
`plot_smooth()`

,
`plot_topo()`

,
`pvisgam()`

# load data: data(simdat) ## Not run: # Condition as factor, to have a random intercept # for illustration purposes: simdat$Condition <- as.factor(simdat$Condition) # Model with random effect and interactions: m2 <- bam(Y ~ s(Time) + s(Trial) + ti(Time, Trial) + s(Condition, bs='re') + s(Time, Subject, bs='fs', m=1), data=simdat) # extract with wrong select value: newd <- inspect_random(m2, select=4) # results in warning, automatically takes select=5 head(newd) inspect_random(m2, select=5, cond=list(Subject=c('a01','a02','a03'))) # Alternatively, fix random effect of Condition, and plot # random effects for subjects with lattice: newd <- inspect_random(m2, select=5, cond=list(Subject=unique(simdat[simdat$Condition==0,'Subject'])), plot=FALSE) # Make lattice plot: require(lattice) lattice::xyplot(fit~Time | Subject, data=newd, type='l', xlab='Time', ylab='Partial effect') # Using argument 'fun': inspect_random(m2, select=5, fun=mean, cond=list(Subject=unique(simdat[simdat$Condition==0,'Subject']))) inspect_random(m2, select=5, fun=mean, cond=list(Subject=unique(simdat[simdat$Condition==2,'Subject'])), col='red', add=TRUE) ## End(Not run) # see the vignette for examples: vignette('overview', package='itsadug')

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.