Description Usage Arguments Details Value References Examples
This function creates an object of class "wblr"
for further processing
by the other functions of wblr.
1 
x 
Either a dataframe containing at least 
s 
An optional vector of rightcensored data, or suspensions. 
interval 
An optional dataframe of interval data having columns specifically named "left" and "right". Left values are the last time at which no failure was evident and may be zero for discovery. Right values are the earliest time at which failure was observed. 
... 
Graphical options for plotting the 
There are several methods to passing arguments for building an wblr
object.
If argument x
is of class "data.frame"
,
then it must contain $time
and $event
columns. Additional columns in the dataframe will be ignored.
When a single unnamed vector of class "numeric"
or "integer"
is supplied, it is treated as a vector
of (life)time observations.
If argument time
or fail
is provided, it is treated as
a vector of (life)time observations. Take care NOT to supply both
time
and fail
in the same function call.
If argument event
is provided, it is treated as
a vector of event indicators with possible values of
0
and 1
. See section "Value" for more details on
event vectors.
If the x
argument is not provided as a dataframe and susp
is provided,
it is treated as a vector of rightcensored (life)time observations
(also called suspended observations or suspensions).
wblr
always generates (probability) plot positions for graphically
displaying the (life)time observations and for (possible) later usage
by wblr.fit
. The following optiona arguments are most appropriate for
passing in with wblr
:
dist
A character string defining the distribution target. When used to establish the basis for
contour mapping (without using wblr.conf
with method.conf="lrb") only "weibull" (default)
and "lognormal" are recognized.
Also used with wblr.fit
for specific fitting control.
pp
Plotting position method, it is a character string describing the method of determining vertical plot positions. Implemented methods are "median" (default), "benard","hazen","mean", "kaplanmeier", and "blom".
rank.adj
The method employed for determining rank of failures when suspensions (right censored data) are present in the data set. Implemented methods are "johnson" (default) and "KMestimator".
ties.handler
The method employed for handling duplicate values in the data set.
Implemented methods are "none" (default) "highest", "lowest", "mean", and "sequential".
It is expected that ties handling will be applied to large data sets that will be fitted
using the maximum likelihood estimation method, where the effect is only on the graphical
presentation. Employing a ties handler on a rank regression model will effectively remove data
from the data set, which is likely not intended.
Use of simply ties
as an argument to function wblr
will silently be accepted as ties.handler
.
par
pch
Point choice defaults to 1
. For more info, see
points
.
cex.points
Point size defaults to 1
.
lwd.points
Line width defaults to 2
.
interval.col
Color defaults to "black"
.
interval.lty
Line type, defaults to "dashed"
.
interval.lwd
Line width defaults to 1
.
Subsequent calls to wblr.fit
and wblr.conf
will inherit these options.
A named list of class "wblr"
. The first list
item ($data
) is a list with up to least three items:
$lrq_frame
A dataframe containing the provided data formatted with "left"
, "right"
, and "qty"
columns.
This is the output of WeibullR function "mleframe"
.
$data$dpoints
A dataframe contianing graphical data for exact failure point with their probability plotting positions and adjusted ranks.
$data$dlines
If interval data has been provided this dataframe will contain the graphical data for display
similar to $data$dpoints
, but with endpoints t1 and t2 for the interval.
William Q. Meeker and Luis A. Escobar, (1998) "Statistical Methods for Reliability Data", WileyInterscience, New York
Robert B. Abernethy, (2008) "The New Weibull Handbook, Fifth Edition"
John I. McCool, (2012) "Using the Weibull Distribution: Reliability, Modeling and Inference"
Jurgen Symynck, Filip De Bal, Weibull analysis using R, in a nutshell (New Technologies and Products in Machine Manufacturing Technology, Stefan cel Mare University of Suceava, 2010).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29  ## These code lines all generate the same object ##
wblr(c(500,1200,900,1300,510))
wblr(time=c(500,1200,900,1300,510))
## this input format works, but not recommended.
wblr(time=c(500,1200,900,1300,510),event=c(1,1,1,1,1))
wblr(fail=c(500,1200,900,1300,510))
wblr(fail=c(500,1200,900,1300,510),susp=c())
da1 < data.frame(
serial=c("S12","S16","S17","S3","S5"),
time=c(500,1200,900,1300,510),
event=c(1,1,1,1,1))
## it is best practice set named objects
obj1 < wblr(da1,label="complete dataset",pch=3,col="orange3")
obj2 < wblr(da1,label="complete dataset",pch=4,pp="benard",col="red")
## Generate a similar dataset, but with suspensions ##
wblr(time=c(500,1200,900,1300,510),event=c(1,1,1,0,0))
wblr(data.frame(time=c(500,1200,900,1300,510),event=c(1,1,1,0,0)))
wblr(fail=c(500,1200,900),susp=c(1300,510))
wblr(time=c(500,1200,900),susp=c(1300,510))
da3 < wblr(fail=c(500,1200,900,1300,510),
event=c(1,1,1,0,0),label="censored dataset",pch=1,col="blue")
## plot datasets ##
## Not run:
plot.wblr(list(da1,da3))
## End(Not run)

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