plot.vargm: Plots the empirical variogram for longitudinal data In joineR: Joint Modelling of Repeated Measurements and Time-to-Event Data

Description

Plots the empirical variogram for observed measurements, of an object of class `vargm`, obtained by using function `variogram`.

Usage

 ```1 2``` ```## S3 method for class 'vargm' plot(x, smooth = FALSE, bdw = NULL, follow.time = NULL, points = TRUE, ...) ```

Arguments

 `x` object of class `vargm` obtained by using function. `variogram` `smooth` logical value to use a non-parametric estimator to calculate the variogram of all v_ijk. The default is `FALSE`, as it uses time averages. `bdw` bandwidth to use in the time averages. The default is `NULL`, because this is calculated automatically. `follow.time` the interval of time we want to construct the variogram for. When `NULL` this is the maximum of the data. `points` logical value if the points v_ijk should be plotted. `...` other graphical options as in `par`.

Value

A graphical device with the plot of empirical variogram.

Ines Sousa

Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```data(mental) mental.unbalanced <- to.unbalanced(mental, id.col = 1, times = c(0, 1, 2, 4, 6, 8), Y.col = 2:7, other.col = c(8, 10, 11)) names(mental.unbalanced)[3] <- "Y" vgm <- variogram(indv = tail(mental.unbalanced[, 1], 30), time = tail(mental.unbalanced[, 2], 30), Y = tail(mental.unbalanced[, 3], 30)) plot(vgm) ```

Example output

```Loading required package: survival
```

joineR documentation built on June 1, 2021, 5:06 p.m.