qad (version 0.2.0)

predict.qad: Predict conditional probabilities

Description

The function predict.qad() predicts the probabilities to end up in specific intervals given x or y values and plots the conditional probabilities. The prediction can be computed in the copula setting or in the data setting.

Usage

# S3 method for qad
predict(
  object,
  values,
  conditioned = c("x1", "x2"),
  nr_intervals = NULL,
  prediction_interval = NULL,
  copula = FALSE,
  pred_plot = FALSE,
  panel.grid = TRUE,
  ...
)

Arguments

object

an object of class 'qad', which determines the underlying checkerboard aggregation.

values

a vector containing the x or the y values for which the conditional probabilities should be predicted.

conditioned

a character specifying on which variable is conditioned. Options are "x1" (default) or "x2".

nr_intervals

an integer, which determines the number of intervals for the prediction. Note, that in the copula setting the intervals are equidistant, in the data setting the retransformed intervals have different lengths. (default = NULL: the number of intervals is the resolution of the checkerboard copula)

prediction_interval

a vector specifying the interval boundaries for which the conditional probability is computed. Options are NULL (default) to predict the conditional probabilites for all intervals or a vector c(lower_boundary, upper_boundary) indicating the boundaries.

copula

a logical (default =FALSE) determining whether the empirical checkerboard copula is used or the retransformed data.

pred_plot

a logical indicating if the conditional probabilites are plotted.

panel.grid

a logical indicating whether the panel.grid is plotted.

...

some methods for this generic require additional arguments. None are used in this method.

Value

a named data.frame and a plot (optional). Each row stands for an evaluation point and the columns contain the conditional probabilities of the intervals.

Examples

# NOT RUN {
n <- 1000
x <- runif(n, -1 ,1)
y <- x^2 + rnorm(n, 0, 1)
sample <- data.frame(x, y)

##(Not Run)
#mod <- qad(sample)
#val <- c(-0.5, 0,1)
#predict(mod, values = val, conditioned = "x1", copula = FALSE, pred_plot = TRUE)
#predict(mod, values = val, conditioned = "x1", copula = TRUE)
#predict(mod, values = val, conditioned = "x1", copula = TRUE, pred_plot = TRUE)


# }