Pareto {EnvStats} | R Documentation |
The Pareto Distribution
Description
Density, distribution function, quantile function, and random generation
for the Pareto distribution with parameters location
and shape
.
Usage
dpareto(x, location, shape = 1)
ppareto(q, location, shape = 1)
qpareto(p, location, shape = 1)
rpareto(n, location, shape = 1)
Arguments
x |
vector of quantiles. |
q |
vector of quantiles. |
p |
vector of probabilities between 0 and 1. |
n |
sample size. If |
location |
vector of (positive) location parameters. |
shape |
vector of (positive) shape parameters. The default is |
Details
Let be a Pareto random variable with parameters
location=
and
shape=
. The density function of
is given by:
The cumulative distribution function of is given by:
and the 'th quantile of
is given by:
The mode, mean, median, variance, and coefficient of variation of are given by:
Value
dpareto
gives the density, ppareto
gives the distribution function,
qpareto
gives the quantile function, and rpareto
generates random
deviates.
Note
The Pareto distribution is named after Vilfredo Pareto (1848-1923), a professor
of economics. It is derived from Pareto's law, which states that the number of
persons having income
is given by:
where denotes Pareto's constant and is the shape parameter for the
probability distribution.
The Pareto distribution takes values on the positive real line. All values must be
larger than the “location” parameter , which is really a threshold
parameter. There are three kinds of Pareto distributions. The one described here
is the Pareto distribution of the first kind. Stable Pareto distributions have
. Note that the
'th moment only exists if
.
The Pareto distribution is related to the
exponential distribution and
logistic distribution as follows.
Let denote a Pareto random variable with
location=
and
shape=
. Then
has an exponential distribution
with parameter
rate=
, and
has a logistic distribution with parameters
location=
and
scale=
.
The Pareto distribution has a very long right-hand tail. It is often applied in the study of socioeconomic data, including the distribution of income, firm size, population, and stock price fluctuations.
Author(s)
Steven P. Millard (EnvStats@ProbStatInfo.com)
References
Forbes, C., M. Evans, N. Hastings, and B. Peacock. (2011). Statistical Distributions. Fourth Edition. John Wiley and Sons, Hoboken, NJ.
Johnson, N. L., S. Kotz, and N. Balakrishnan. (1994). Continuous Univariate Distributions, Volume 1. Second Edition. John Wiley and Sons, New York.
See Also
epareto
, eqpareto
, Exponential,
Probability Distributions and Random Numbers.
Examples
# Density of a Pareto distribution with parameters location=1 and shape=1,
# evaluated at 2, 3 and 4:
dpareto(2:4, 1, 1)
#[1] 0.2500000 0.1111111 0.0625000
#----------
# The cdf of a Pareto distribution with parameters location=2 and shape=1,
# evaluated at 3, 4, and 5:
ppareto(3:5, 2, 1)
#[1] 0.3333333 0.5000000 0.6000000
#----------
# The 25'th percentile of a Pareto distribution with parameters
# location=1 and shape=1:
qpareto(0.25, 1, 1)
#[1] 1.333333
#----------
# A random sample of 4 numbers from a Pareto distribution with parameters
# location=3 and shape=2.
# (Note: the call to set.seed simply allows you to reproduce this example.)
set.seed(10)
rpareto(4, 3, 2)
#[1] 4.274728 3.603148 3.962862 5.415322