Geometric inverse cumulative distribution function
x = geoinv(y,p)
x = geoinv(y,p) returns
the inverse cumulative distribution function (icdf) of the geometric
distribution at each value in
y using the corresponding
geoinv returns the smallest positive integer
that the geometric cdf evaluated at
x is equal
to or exceeds
y. You can think of
the probability of observing
x successes in a row
in independent trials, where
p is the probability
of success in each trial.
p can be vectors,
matrices, or multidimensional arrays that all have the same size.
A scalar input for
expanded to a constant array with the same dimensions as the other
input. The values in
lie on the interval
Compute Geometric Distribution icdf
Suppose the probability of a five-year-old car battery not starting in cold weather is 0.03. If we want no more than a ten percent chance that the car does not start, what is the maximum number of days in a row that we should try to start the car?
To solve, compute the inverse cdf of the geometric distribution. In this example, a "success" means the car does not start, while a "failure" means the car does start. The probability of success for each trial p equals 0.03, while the probability of observing x failures in a row before observing a success y equals 0.1.
y = 0.1; p = 0.03; x = geoinv(y,p)
x = 3
The returned result indicates that if we start the car three times, there is at least a ten percent chance that it will not start on one of those tries. Therefore, if we want no greater than a ten percent chance that the car will not start, we should only attempt to start it for a maximum of two days in a row.
We can confirm this result by evaluating the cdf at values of x equal to 2 and 3, given the probability of success for each trial p equal to 0.03.
y2 = geocdf(2,p) % cdf for x = 2
y2 = 0.0873
y3 = geocdf(3,p) % cdf for x = 3
y3 = 0.1147
The returned results indicate an 8.7% chance of the car not starting if we try two days in a row, and an 11.5% chance of not starting if we try three days in a row.
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Introduced before R2006a