wblinv
Weibull inverse cumulative distribution function
Syntax
X = wblinv(P,A,B)
[X,XLO,XUP] = wblinv(P,A,B,PCOV,alpha)
Description
X = wblinv(P,A,B)
returns the inverse cumulative
distribution function (cdf) for a Weibull distribution with scale
parameter A
and shape parameter B
,
evaluated at the values in P
. P
, A
,
and B
can be vectors, matrices, or multidimensional
arrays that all have the same size. A scalar input is expanded to
a constant array of the same size as the other inputs. The default
values for A
and B
are both 1
.
[X,XLO,XUP] = wblinv(P,A,B,PCOV,alpha)
returns
confidence bounds for X
when the input parameters A
and B
are
estimates. PCOV
is a 2-by-2 matrix containing the
covariance matrix of the estimated parameters. alpha
has
a default value of 0.05, and specifies 100(1 - alpha
)% confidence bounds. XLO
and XUP
are
arrays of the same size as X
containing the lower
and upper confidence bounds.
The function wblinv
computes confidence bounds
for X
using a normal approximation to the distribution
of the estimate
where q is the P
th quantile
from a Weibull distribution with scale and shape parameters both equal
to 1. The computed bounds give approximately the desired confidence
level when you estimate mu
, sigma
,
and PCOV
from large samples, but in smaller samples
other methods of computing the confidence bounds might be more accurate.
The inverse of the Weibull cdf is
Examples
The lifetimes (in hours) of a batch of light bulbs has a Weibull
distribution with parameters a
= 200
and b = 6
.
Find the median lifetime of the bulbs:
life = wblinv(0.5, 200, 6) life = 188.1486
Generate 100 random values from this distribution, and estimate the 90th percentile (with confidence bounds) from the random sample
x = wblrnd(200,6,100,1); p = wblfit(x) [nlogl,pcov] = wbllike(p,x) [q90,q90lo,q90up] = wblinv(0.9,p(1),p(2),pcov) p = 204.8918 6.3920 nlogl = 496.8915 pcov = 11.3392 0.5233 0.5233 0.2573 q90 = 233.4489 q90lo = 226.0092 q90up = 241.1335
Extended Capabilities
Version History
Introduced before R2006a