| Title: | Use the MLS Junk Generator Algorithm to Generate a Stream of Pseudo-Random Numbers |
|---|---|
| Description: | Generate a stream of pseudo-random numbers generated using the MLS Junk Generator algorithm. Functions exist to generate single pseudo-random numbers as well as a vector, data frame, or matrix of pseudo-random numbers. |
| Authors: | Steve Myles [aut, cre] |
| Maintainer: | Steve Myles <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.1.2 |
| Built: | 2025-02-05 03:09:48 UTC |
| Source: | https://github.com/scumdogsteev/mlsjunkgen |
Based on user input seeds, this function generates a pseudo-random number. This is called by the mlsjunkgen package's other functions to generate a pseudo-random number stream.
junkgen(w, x, y, z)junkgen(w, x, y, z)
w |
the first seed required by the MLS Junk Generator algorithm |
x |
the first seed required by the MLS Junk Generator algorithm |
y |
the first seed required by the MLS Junk Generator algorithm |
z |
the first seed required by the MLS Junk Generator algorithm |
A numeric vector containing a single pseudo-random number
# Generate a pseudo-random number with user-specified seeds w <- 1 x <- 2 y <- 3 z <- 4 junkgen(w = w, x = x, y = y, z = z) # returns "[1] 0.9551644"# Generate a pseudo-random number with user-specified seeds w <- 1 x <- 2 y <- 3 z <- 4 junkgen(w = w, x = x, y = y, z = z) # returns "[1] 0.9551644"
mlsjunkgen: Use the MLS Junk Generator Algorithm to Generate a Stream of Pseudo-Random Numbers
junkgen: generate a single pseudo-random number; called by the other functions
mlsjunkgenv: generate a vector stream of pseudo-random numbers
mlsjunkgend: generate a data frame of pseudo-random numbers
mlsjunkgenm: generate a matrix of pseudo-random numbers
Based on user input seeds, this function generates a data frame of n pseudo-random numbers and names the column containing these as "RN" for "random numbers." This is achieved by calling junkgen.
mlsjunkgend(n = 1, w, x, y, z, round = 5)mlsjunkgend(n = 1, w, x, y, z, round = 5)
n |
the number of pseudo-random numbers to generate; defaults to 1 |
w |
the first seed required by the MLS Junk Generator algorithm |
x |
the first seed required by the MLS Junk Generator algorithm |
y |
the first seed required by the MLS Junk Generator algorithm |
z |
the first seed required by the MLS Junk Generator algorithm |
round |
the number of decimal places to which to round the pseudo-random numbers; default = 5 |
A numeric vector containing a single pseudo-random number
# Generate a pseudo-random number data frame with 10 observations from user-specified seeds w <- 1 x <- 2 y <- 3 z <- 4 mlsjunkgend(n = 10, w = w, x = x, y = y, z = z) # returns a data frame of 10 observations # Specifying different values for n and round mlsjunkgend(n = 5, w = w, x = x, y = y, z = z, round = 2) # returns a data frame identical to the above example but with only 5 observations # rounded to 2 decimal places # using the default value of n (1) is identical to assigning the rounded result of # junkgen to a data frame of 1 observation round(junkgen(w = w, x = x, y = y, z = z), 5) # returns "[1] 0.95516" mlsjunkgend(w = w, x = x, y = y, z = z) # returns the following: # RN # 1 0.95516# Generate a pseudo-random number data frame with 10 observations from user-specified seeds w <- 1 x <- 2 y <- 3 z <- 4 mlsjunkgend(n = 10, w = w, x = x, y = y, z = z) # returns a data frame of 10 observations # Specifying different values for n and round mlsjunkgend(n = 5, w = w, x = x, y = y, z = z, round = 2) # returns a data frame identical to the above example but with only 5 observations # rounded to 2 decimal places # using the default value of n (1) is identical to assigning the rounded result of # junkgen to a data frame of 1 observation round(junkgen(w = w, x = x, y = y, z = z), 5) # returns "[1] 0.95516" mlsjunkgend(w = w, x = x, y = y, z = z) # returns the following: # RN # 1 0.95516
Based on user input seeds, this function generates a vector of n pseudo-random numbers by calling mlsjunkgenv which in turn calls junkgen.
mlsjunkgenm(nrow = 1, ncol = 1, w, x, y, z, round = 5)mlsjunkgenm(nrow = 1, ncol = 1, w, x, y, z, round = 5)
nrow |
the number of rows for the matrix; defaults to 1 |
ncol |
the number of columns for the matrix; defaults to 1 |
w |
the first seed required by the MLS Junk Generator algorithm |
x |
the first seed required by the MLS Junk Generator algorithm |
y |
the first seed required by the MLS Junk Generator algorithm |
z |
the first seed required by the MLS Junk Generator algorithm |
round |
the number of decimal places to which to round the pseudo-random numbers; default = 5 |
A numeric vector containing a single pseudo-random number
# Generate a 4x4 matrix of pseudo-random numbers with user-specified seeds w <- 1 x <- 2 y <- 3 z <- 4 mlsjunkgenm(nrow = 4, ncol = 4, w = w, x = x, y = y, z = z) # returns a 4x4 matrix # the sixteen values in the above matrix are equivalent to the following call # to mlsjunkgenv mlsjunkgenv(n = 16, w = w, x = x, y = y, z = z) # matrices need not be square # this returns a 3x2 matrix of pseudo-random numbers with 2 decimal places mlsjunkgenm(nrow = 3, ncol = 2, w = w, x = x, y = y, z = z, round = 2) # using the default value of n (1) generates a 1x1 matrix the value of which # is identical to running junkgen and rounding the result to 5 decimal places round(junkgen(w = w, x = x, y = y, z = z), 5) # returns "[1] 0.95516" mlsjunkgenv(w = w, x = x, y = y, z = z) # returns a 1x1 matrix with single element = "0.95516"# Generate a 4x4 matrix of pseudo-random numbers with user-specified seeds w <- 1 x <- 2 y <- 3 z <- 4 mlsjunkgenm(nrow = 4, ncol = 4, w = w, x = x, y = y, z = z) # returns a 4x4 matrix # the sixteen values in the above matrix are equivalent to the following call # to mlsjunkgenv mlsjunkgenv(n = 16, w = w, x = x, y = y, z = z) # matrices need not be square # this returns a 3x2 matrix of pseudo-random numbers with 2 decimal places mlsjunkgenm(nrow = 3, ncol = 2, w = w, x = x, y = y, z = z, round = 2) # using the default value of n (1) generates a 1x1 matrix the value of which # is identical to running junkgen and rounding the result to 5 decimal places round(junkgen(w = w, x = x, y = y, z = z), 5) # returns "[1] 0.95516" mlsjunkgenv(w = w, x = x, y = y, z = z) # returns a 1x1 matrix with single element = "0.95516"
Based on user input seeds, this function generates a vector of n pseudo-random numbers by calling junkgen.
mlsjunkgenv(n = 1, w, x, y, z, round = 5)mlsjunkgenv(n = 1, w, x, y, z, round = 5)
n |
the number of pseudo-random numbers to generate; defaults to 1 |
w |
the first seed required by the MLS Junk Generator algorithm |
x |
the first seed required by the MLS Junk Generator algorithm |
y |
the first seed required by the MLS Junk Generator algorithm |
z |
the first seed required by the MLS Junk Generator algorithm |
round |
the number of decimal places to which to round the pseudo-random numbers; default = 5 |
A numeric vector containing a single pseudo-random number
# Generate a pseudo-random number stream of length 5 with user-specified seeds w <- 1 x <- 2 y <- 3 z <- 4 # the following call returns "[1] 0.95516 0.66908 0.21235 0.34488 0.11995" mlsjunkgenv(n = 5, w = w, x = x, y = y, z = z) # Specifying different values for n and round mlsjunkgenv(n = 3, w = w, x = x, y = y, z = z, round = 2) # returns "[1] 0.96 0.67 0.21" # using the default value of n (1) is identical to running junkgen and rounding # the result to 5 decimal places round(junkgen(w = w, x = x, y = y, z = z),5) # returns "[1] 0.95516" mlsjunkgenv(w = w, x = x, y = y, z = z) # returns "[1] 0.95516"# Generate a pseudo-random number stream of length 5 with user-specified seeds w <- 1 x <- 2 y <- 3 z <- 4 # the following call returns "[1] 0.95516 0.66908 0.21235 0.34488 0.11995" mlsjunkgenv(n = 5, w = w, x = x, y = y, z = z) # Specifying different values for n and round mlsjunkgenv(n = 3, w = w, x = x, y = y, z = z, round = 2) # returns "[1] 0.96 0.67 0.21" # using the default value of n (1) is identical to running junkgen and rounding # the result to 5 decimal places round(junkgen(w = w, x = x, y = y, z = z),5) # returns "[1] 0.95516" mlsjunkgenv(w = w, x = x, y = y, z = z) # returns "[1] 0.95516"