Uniform
The Uniform Distribution
Description
    Calculates density, cumulative probability, quantile, and 
    generates a random sample for the uniform distribution (continuous).
Usage
dunif(x, min = 0, max = 1, log = FALSE) # density
punif(q, min = 0, max = 1, lower.tail = TRUE, log.p = FALSE) # probability
qunif(p, min = 0, max = 1, lower.tail = TRUE, log.p = FALSE) # quantile
runif(n, min = 0, max = 1) # random
Arguments
    
| x, q | numeric vectors in the range [min, max] that specify 
        the quantiles. | 
    | p | a numeric vector in the range [0, 1] that specifies the 
        probabilities. | 
    | n | an integer in the range [0, Inf) that specifies the number of 
        random samples requested.
        If the input value is not an integer, it is truncated.
        If length(n) is greater than 1,
        the random function returns length(n) random samples. | 
    | min | a numeric vector in the range (-Inf, Inf) that specifies lower 
        limits. In the case of runif, min to max 
        is an open interval unless min = max. That is, 
        if min = 0 and max = 1, then no random numbers 
        will ever be exactly 0 or 1. | 
    | max | a numeric vector in the range (-Inf, Inf) that specifies upper 
        limits, which are greater than or equal to lower limits 
        specified in min. In the case of runif, 
        min to max is an open interval unless min 
        = max. That is, if min = 0 and max = 1, 
        then no random numbers will ever be exactly 0 or 
        1. | 
    | log | a logical value. If FALSE (default), the density 
        function returns the density itself. If TRUE, it 
        returns the log of the density. | 
    | lower.tail | a logical value. If TRUE (default), the probability 
        supplied to the quantile function or returned by the 
        probability function is P[X <= x]. If FALSE, it 
        is P[X > x]. | 
    | log.p | a logical value. If FALSE (default), the probability 
        supplied to the quantile function or returned by the 
        probability function is the probability itself. If 
        TRUE, it is the log of the probability. | 
 
Details
    The distribution parameter(s) are replicated cyclically to be the 
    same length as the input x, q, p, or the 
    number of random samples requested.
    Missing values (NAs) in the input or the distribution 
    parameter(s) will cause the corresponding elements of the result 
    to be missing.
Value
    returns returns density (dunif), 
    cumulative probability (punif), 
    quantile (qunif), or 
    random sample (runif) 
    for the uniform distribution with parameters min and max.
Side Effects
    If the .Random.seed dataset exists, the random sample 
    function updates its value.
    The random sample function creates the .Random.seed dataset 
    if it does not exist.
Background
    The uniform distribution is a family of continuous probability 
    distributions defined on the interval [min, max] and 
    parameterized by two parameters, min and max.
    The uniform (or rectangular) distribution takes values equally 
    likely from min to max. The uniform distribution has 
    several uses but it is commonly used to model round-off errors.
    
    
    
    
    
    
    
    
    
    
References
    Johnson, N. L. and Kotz, S. (1970). 
    Continuous Univariate Distributions, vol. 2.
    Houghton-Mifflin, Boston. 
Differences between Spotfire Enterprise Runtime for R and Open-source R
-  In open-source R, min = max is allowed for {p,q,r}unif but dunif(2, 2, 2) returns NaN and generates a warning.
-  In Spotfire Enterprise Runtime for R, min = max is allowed for all {d,p,q,r}unif and dunif(2, 2, 2) returns Inf.
 
See Also
    set.seed, To generate a uniform sample on integers or populations use 
sample.
 
Examples
x <- 1:10
x + runif(x)   # jitter the x data $
runif(100, -1, 1) # 100 numbers uniform on -1 to 1