statprops {ipptoolbox} | R Documentation |
Functions for various different statistical properties of a BPA.
dsaggwidth(x) dsconf(x, conf, confconf = NULL) dsexpect(x) dsvariance(x) dsbelpl(x, a) dssummary(x)
x |
BPA |
conf |
Confidence level in ]0,1[ |
confconf |
Wilk's confidence bounds in ]0,1[ on the conf (if empty, ommitted). |
a |
Interval for Bel(x in a), Pl(x in a) |
Various different statistical properties of a BPA: Aggregated width (dsaggwidth), expected value (dsexpect), quantiles (dsconf), variance (dsvariance) and Belief/Plausibility (dsbelpl). The function dsconf is also able to return Wilks' bounds for a given confidence level. The function dssummary is the analogue to a summary statistics and computes a lot of statistics at once.
The example calculates a set of statistical properties of a pbox x.
Statistical property of a BPA (interval). dssummary returns a list of statistics.
Philipp Limbourg <p.limbourg@uni-due.de>
Kreinovich, V., G. Xiang, et al. (2006). "Computing mean and variance under Dempster-Shafer uncertainty: Towards faster algorithms." International Journal of Approximate Reasoning 42(3): 212-227.
mu=dsstruct(c(10,12,1)) sigma=dsstruct(c(1,1.5,1)) x=dsadf('qnorm',1000,mu,sigma) print("Sample of 1000 focal elements from a normal dist") print("Mean:") print(dsexpect(x)) print("Variance:") print(dsvariance(x)) print("Median:") print(dsconf(x,0.5)) print("Bel and Pl of x in [4,8]:") print(dsbelpl(x,c(4,8))) print("Aggregated width:") print(dsaggwidth(x)) print("95 percent conf. level with 95 percent Wilks bounds") print(dsconf(x,0.95,0.95)) print("Summary statistics") print(dssummary(x))