| plot.DTDAni {DTDA.ni} | R Documentation |
plot.DTDAni
Description
S3 method to plot a DTDAni object by using the generic plot function.
Usage
## S3 method for class 'DTDAni'
plot(x, ecdf = FALSE, ...)
Arguments
x |
DTDAni object. |
ecdf |
Whether to display the ordinary empirical cumulative distribution function or not. Default = FALSE. |
... |
Aditional parameters. |
Acknowledgements
Jacobo de Uña-Álvarez was supported by Grant MTM2014-55966-P, Spanish Ministry of Economy and Competitiveness.
José Carlos Soage was supported by Red Tecnológica de Matemática Industrial (Red TMATI), Cons. de Cultura, Educación e OU, Xunta de Galicia (ED341D R2016/051) and by Grupos de Referencia Competitiva, Consolidación y Estructuración de Unidades de Investigación Competitivas del SUG, Cons. de Cultura, Educación e OU, Xunta de Galicia (GRC ED431C 2016/040).
Author(s)
de Uña-Álvarez, Jacobo.
Soage González, José Carlos.
Maintainer: José Carlos Soage González. jsoage@uvigo.es
References
de Uña-Álvarez J. (2018) A Non-iterative Estimator for Interval Sampling and Doubly Truncated Data. In: Gil E., Gil E., Gil J., Gil M. (eds) The Mathematics of the Uncertain. Studies in Systems, Decision and Control, vol 142. Springer, Cham, pp. 387-400.
Examples
## Not run:
N <- 250
x0 <- runif(N) # Original data
u0 <- runif(N, -0.25, 0.5) # Left-truncation times
tau <- 0.75 # Interval width
v0 <- u0 + tau
x <- x0[u0 <= x0 & x0 <= v0]
u <- u0[u0 <= x0 & x0 <= v0]
v <- v0[u0 <= x0 & x0 <= v0]
n <- length(x) # Final sample size after the interval sampling
res <- DTDAni(x, u , tau)
plot(res)
plot(res, ecdf = TRUE)
## End(Not run)