An R
-package for the Nakagami distribution.
Use the following command from inside R
:
The density function is dnaka
, the probability distribution is pnaka
, the quantile function is qnaka
and random deviate generator is rnaka
. Use them just like the *gamma
functions in the stats
package.
set.seed(313)
x = seq(0, 3, by = 0.01)
hist(nakagami::rnaka(10^5, shape = 4, scale = 2), freq = FALSE, breaks = "FD")
lines(x, nakagami::dnaka(x, shape = 4, scale = 2), type = "l", lwd = 2)
All of these functions are implemented in the R
package VGAM
. As of VGAM
version 1.1-2, the implementations in nakagami
are faster, more thoroughly tested, and use a standardized set of arguments following the template of dgamma
et cetera.
The rnaka
of nakagami
is much faster than the rnaka
of VGAM
:
#install.packages("VGAM")
microbenchmark::microbenchmark(nakagami::rnaka(100, 2, 4),
VGAM::rnaka(100, 4, 2))
#> Unit: microseconds
#> expr min lq mean median uq
#> nakagami::rnaka(100, 2, 4) 265.9 303.45 553.702 352.6 430.25
#> VGAM::rnaka(100, 4, 2) 2028.3 2355.35 17558.350 2670.4 3040.85
#> max neval
#> 15697.2 100
#> 1480179.6 100
And the quantile function of nakagami
is slightly faster.
p = 1:10/11
microbenchmark::microbenchmark(nakagami::qnaka(0.01, 10, 4),
VGAM::qnaka(0.01, 4, 10))
#> Unit: microseconds
#> expr min lq mean median uq max
#> nakagami::qnaka(0.01, 10, 4) 143.6 170.10 2117.254 201.65 293.25 183790.6
#> VGAM::qnaka(0.01, 4, 10) 345.9 389.55 565.839 464.65 585.10 2706.5
#> neval
#> 100
#> 100
Moreover, VGAM::qnaka
fails to implement the standard argument log.p
and VGAM::rnaka
uses the non-standard arguments Smallno
and ...
.
If you encounter a bug, have a feature request or need some help, open a Github issue.
This project follows a Contributor Code of Conduct.
Nakagami, N. 1960. “The m-Distribution, a General Formula of Intensity of Rapid Fading.” In Statistical Methods in Radio Wave Propagation: Proceedings of a Symposium Held at the University of California, June 18–20, 1958, edited by William C. Hoffman, 3–36. Permagon Press. https://doi.org/10.1016/B978-0-08-009306-2.50005-4.
Yee TW (2010). “The VGAM Package for Categorical Data Analysis.” Journal of Statistical Software, 32(10), 1–34. https://www.jstatsoft.org/v32/i10/.