idf: Interval data frame

In linLIR: linear Likelihood-based Imprecise Regression

Description

Create an interval data frame (idf-object), summarize its content and visualize subsets of two variables.

Usage

idf.create(dat, var.labels = NULL)

## S3 method for class 'idf'
summary(object, ...)
## S3 method for class 'idf'
plot(x, y=NULL, ..., var = NULL, typ="hist", k.x = 1, k.y = 1, inf.margin=10, p.cex=1, col.lev=15, plot.grid=FALSE, x.adj = 0.5, x.padj = 3, y.las = 0, y.adj = 1, y.padj = 0, x.lim = c(0, 0), y.lim = c(0, 0), x.lab = "X", y.lab = "Y")

Arguments

dat	A data.frame containing 2 neighboring columns for each variable, the first column for the left endpoints of the interval observations, the second for the right endpoints.
var.labels	Names of the variables corresponding to the interval-valued observations in the data.frame.
object	The idf-object to be summarized.
...	Argument of the generic functions plot and summary: Other parameters.
x	Argument of the generic function plot. Here x is the idf-object to be plotted.
y	Argument of the generic function plot. Here y=NULL.
var	Names of the two variables out of the idf-object to be plotted. (Optional)
typ	Type of the plot. Possible values are "hist": plot 2-dim. histogram (default) and "draft".
k.x	Particular plot function parameter. 1/k.x is the step width along the abscissa.
k.y	Particular plot function parameter. 1/k.y is the step width along the ordinate.
inf.margin	Particular parameter for plot type "draft". inf.margin is the number of steps that the infinite observations are drawn beyond the limits of the plot.
p.cex	Particular parameter for plot type "draft". p.cex is the point size to fill the rectangles with grey color.
col.lev	Particular parameter for plot type "hist" indicating the number of different grey levels in the 2-dim. histogram.
plot.grid	Logical for plot type "hist". If plot.grid=TRUE dashed lines are added to the plot to indicate the location of the interval endpoints. This is particularly useful for categorized data.
x.adj	Horizontal position of the text for the abscissa.
x.padj	Vertical position of the text for the abscissa.
y.las	Orientation of the text for the ordinate. y.las=1 will turn the axis labels and the text in reading direction.
y.adj	y.adj regulates the position of the text for the ordinate in reading direction, i.e. if y.las=0 it sets the vertical position and if y.las=1 the horizontal position.
y.padj	y.padj regulates the position of the text for the ordinate orthogonal to the reading direction, i.e. if y.las=0 it sets the horizontal position and if y.las=1 the vertical position.
x.lim	The limits for the abscissa of the plot.
y.lim	The limits for the ordinate of the plot.
x.lab	Title of the abscissa.
y.lab	Title of the ordinate.

Details

Within the LIR framework all types of interval data are possible, including the particular cases of actually precise data (i.e., lower endpoint = upper endpoint) or missing data (i.e., in case of a real valued variable, lower endpoint = -Inf and upper endpoint = Inf). For the LIR analysis it makes practically no difference if the intervals are closed or not, therefore, the created idf-object does not contain this information.

Value

An idf-object of m variables, which is a list of m+1 entries.

Var1 ... varm	m different data.frames with 2 columns each, one for each of the 1st to mth variables.
n	Number of observations.

References

M. Cattaneo, A. Wiencierz (2012c). On the implementation of LIR: the case of simple linear regression with interval data. Technical Report No. 127. Department of Statistics. LMU Munich.

A. Wiencierz, M. Cattaneo (2012b). An exact algorithm for Likelihood-based Imprecise Regression in the case of simple linear regression with interval data. In: R. Kruse et al. (Eds.). Advances in Intelligent Systems and Computing. Vol. 190. Springer. pp. 293-301.

M. Cattaneo, A. Wiencierz (2012a). Likelihood-based Imprecise Regression. International Journal of Approximate Reasoning. Vol. 53. pp. 1137-1154.

Examples

data('toy.smps')
toy.idf <- idf.create(toy.smps, var.labels=c("x","y"))

summary(toy.idf)

plot(toy.idf, typ="draft", k.x=10, k.y=10, p.cex=1.5, y.las=1, y.adj=6) 
plot(toy.idf, typ="draft", k.x=10, k.y=10, x.adj=0.7, y.las=1, y.adj=6, y.padj=-3)
plot(toy.idf, k.x=10, k.y=10, x.adj=0.7, x.padj=4, y.adj=0.7, y.padj=-4)

data('pm10')
pm.idf <- idf.create(pm10)

summary(pm.idf)

plot(pm.idf, typ="draft", k.x=10, k.y=20, p.cex=0.35, x.adj=0.5, x.padj=4, y.las=0, y.adj=0.5, y.padj=-4, x.lab="temperature", y.lab="particulate matter concentration")

linLIR documentation built on May 2, 2019, 3:48 p.m.