[整理] 利用R生成随机分布的…
发布日期:2021-10-16 07:12:17 浏览次数:6 分类:技术文章

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[整理] 利用R生成随机分布的方法
文/周庭锐

夜里复习各种统计分布的模拟、拟合、验证的R编程,顺手整理一下。
(不懂怎么一回事,刚刚贴上了,然后一转眼就消失了。新浪博客里闹鬼?)

d: density
p: distribution function
q: quantile function
r: random deviates

rexp The Exponential Distribution
      dexp(x, rate = 1, log = FALSE)
      pexp(q, rate = 1, lower.tail = TRUE, log.p = FALSE)
      qexp(p, rate = 1, lower.tail = TRUE, log.p = FALSE)
      rexp(n, rate = 1)

rf The F Distribution
      df(x, df1, df2, ncp, log = FALSE)
      pf(q, df1, df2, ncp, lower.tail = TRUE, log.p = FALSE)
      qf(p, df1, df2, ncp, lower.tail = TRUE, log.p = FALSE)
      rf(n, df1, df2, ncp)

rgamma The Gamma Distribution
      dgamma(x, shape, rate = 1, scale = 1/rate, log = FALSE)
      pgamma(q, shape, rate = 1, scale = 1/rate, lower.tail = TRUE, log.p = FALSE)
      qgamma(p, shape, rate = 1, scale = 1/rate, lower.tail = TRUE, log.p = FALSE)
      rgamma(n, shape, rate = 1, scale = 1/rate)

rgeom The Geometric Distribution
      dgeom(x, prob, log = FALSE)
      pgeom(q, prob, lower.tail = TRUE, log.p = FALSE)
      qgeom(p, prob, lower.tail = TRUE, log.p = FALSE)
      rgeom(n, prob)

rhyper The Hypergeometric Distribution
      dhyper(x, m, n, k, log = FALSE)
      phyper(q, m, n, k, lower.tail = TRUE, log.p = FALSE)
      qhyper(p, m, n, k, lower.tail = TRUE, log.p = FALSE)
      rhyper(nn, m, n, k)

rlnorm The Log Normal Distribution
      dlnorm(x, meanlog = 0, sdlog = 1, log = FALSE)
      plnorm(q, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE)
      qlnorm(p, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE)
      rlnorm(n, meanlog = 0, sdlog = 1)

rlogis The Logistic Distribution
      dlogis(x, location = 0, scale = 1, log = FALSE)
      plogis(q, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE)
      qlogis(p, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE)
      rlogis(n, location = 0, scale = 1)

rmultinom The Multinomial Distribution
      rmultinom(n, size, prob)
      dmultinom(x, size = NULL, prob, log = FALSE)

rnbinom The Negative Binomial Distribution
      dnbinom(x, size, prob, mu, log = FALSE)
      pnbinom(q, size, prob, mu, lower.tail = TRUE, log.p = FALSE)
      qnbinom(p, size, prob, mu, lower.tail = TRUE, log.p = FALSE)
      rnbinom(n, size, prob, mu)

rnorm The Normal Distribution
      dnorm(x, mean = 0, sd = 1, log = FALSE)
      pnorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)
      qnorm(p, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)
      rnorm(n, mean = 0, sd = 1)

rpois The Poisson Distribution
      dpois(x, lambda, log = FALSE)
      ppois(q, lambda, lower.tail = TRUE, log.p = FALSE)
      qpois(p, lambda, lower.tail = TRUE, log.p = FALSE)
      rpois(n, lambda)

rsignrank Distribution of the Wilcoxon Signed Rank Statistic
      dsignrank(x, n, log = FALSE)
      psignrank(q, n, lower.tail = TRUE, log.p = FALSE)
      qsignrank(p, n, lower.tail = TRUE, log.p = FALSE)
      rsignrank(nn, n)

rt The Student t Distribution
      dt(x, df, ncp, log = FALSE)
      pt(q, df, ncp, lower.tail = TRUE, log.p = FALSE)
      qt(p, df, ncp, lower.tail = TRUE, log.p = FALSE)
      rt(n, df, ncp)

runif The Uniform Distribution
      dunif(x, min=0, max=1, log = FALSE)
      punif(q, min=0, max=1, lower.tail = TRUE, log.p = FALSE)
      qunif(p, min=0, max=1, lower.tail = TRUE, log.p = FALSE)
      runif(n, min=0, max=1)

rweibull The Weibull Distribution
      dweibull(x, shape, scale = 1, log = FALSE)
      pweibull(q, shape, scale = 1, lower.tail = TRUE, log.p = FALSE)
      qweibull(p, shape, scale = 1, lower.tail = TRUE, log.p = FALSE)
      rweibull(n, shape, scale = 1)

rwilcox Distribution of the Wilcoxon Rank Sum Statistic
      dwilcox(x, m, n, log = FALSE)
      pwilcox(q, m, n, lower.tail = TRUE, log.p = FALSE)
      qwilcox(p, m, n, lower.tail = TRUE, log.p = FALSE)
      rwilcox(nn, m, n)

sample The Discrete Uniform Distribution
      sample(x, size, replace = FALSE, prob = NULL)
      sample.int(n, size = n, replace = FALSE, prob = NULL)

拟合:
连续型变量:
大样本:Kolmogorov-Smirnov检验
      ks.test(x, y, ...,
              alternative = c("two.sided", "less", "greater"),
              exact = NULL)
小样本:Shapiro-Wilk检验
      shapiro.test(x)

离散型变量:方差齐次性检验
      fligner.test(x, ...)
     
      ## Default S3 method:
      fligner.test(x, g, ...)
     
      ## S3 method for class 'formula'
      fligner.test(formula, data, subset, na.action, ...)
      mood.test(x, ...)
     
      ## Default S3 method:
      mood.test(x, y,
                alternative = c("two.sided", "less", "greater"), ...)
     
      ## S3 method for class 'formula'
      mood.test(formula, data, subset, na.action, ...)

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