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Random Number Generation

Source: R/burrrIII3.R, R/gamma.R, R/gompertz.R, and 9 more
ssd_r.Rd

Random Number Generation

Usage

ssd_rburrIII3(n, shape1 = 1, shape2 = 1, scale = 1, chk = TRUE)

ssd_rgamma(n, shape = 1, scale = 1, chk = TRUE)

ssd_rgompertz(n, location = 1, shape = 1, chk = TRUE)

ssd_rinvpareto(n, shape = 3, scale = 1, chk = TRUE)

ssd_rlgumbel(n, locationlog = 0, scalelog = 1, chk = TRUE)

ssd_rllogis_llogis(
  n,
  locationlog1 = 0,
  scalelog1 = 1,
  locationlog2 = 1,
  scalelog2 = 1,
  pmix = 0.5,
  chk = TRUE
)

ssd_rllogis(n, locationlog = 0, scalelog = 1, chk = TRUE)

ssd_rlnorm_lnorm(
  n,
  meanlog1 = 0,
  sdlog1 = 1,
  meanlog2 = 1,
  sdlog2 = 1,
  pmix = 0.5,
  chk = TRUE
)

ssd_rlnorm(n, meanlog = 0, sdlog = 1, chk = TRUE)

ssd_rmulti(
  n,
  burrIII3.weight = 0,
  burrIII3.shape1 = 1,
  burrIII3.shape2 = 1,
  burrIII3.scale = 1,
  gamma.weight = 0,
  gamma.shape = 1,
  gamma.scale = 1,
  gompertz.weight = 0,
  gompertz.location = 1,
  gompertz.shape = 1,
  invpareto.weight = 0,
  invpareto.shape = 3,
  invpareto.scale = 1,
  lgumbel.weight = 0,
  lgumbel.locationlog = 0,
  lgumbel.scalelog = 1,
  llogis.weight = 0,
  llogis.locationlog = 0,
  llogis.scalelog = 1,
  llogis_llogis.weight = 0,
  llogis_llogis.locationlog1 = 0,
  llogis_llogis.scalelog1 = 1,
  llogis_llogis.locationlog2 = 1,
  llogis_llogis.scalelog2 = 1,
  llogis_llogis.pmix = 0.5,
  lnorm.weight = 1,
  lnorm.meanlog = 0,
  lnorm.sdlog = 1,
  lnorm_lnorm.weight = 0,
  lnorm_lnorm.meanlog1 = 0,
  lnorm_lnorm.sdlog1 = 1,
  lnorm_lnorm.meanlog2 = 1,
  lnorm_lnorm.sdlog2 = 1,
  lnorm_lnorm.pmix = 0.5,
  weibull.weight = 0,
  weibull.shape = 1,
  weibull.scale = 1,
  chk = TRUE
)

ssd_rweibull(n, shape = 1, scale = 1, chk = TRUE)

Arguments

n

positive number of observations.

shape1

shape1 parameter.

shape2

shape2 parameter.

scale

scale parameter.

chk

A flag specifying whether to check the arguments.

shape

shape parameter.

location

location parameter.

locationlog

location on the log scale parameter.

scalelog

scale on log scale parameter.

locationlog1

locationlog1 parameter.

scalelog1

scalelog1 parameter.

locationlog2

locationlog2 parameter.

scalelog2

scalelog2 parameter.

pmix

Proportion mixture parameter.

meanlog1

mean on log scale parameter.

sdlog1

standard deviation on log scale parameter.

meanlog2

mean on log scale parameter.

sdlog2

standard deviation on log scale parameter.

meanlog

mean on log scale parameter.

sdlog

standard deviation on log scale parameter.

burrIII3.weight

weight parameter for the Burr III distribution.

burrIII3.shape1

shape1 parameter for the Burr III distribution.

burrIII3.shape2

shape2 parameter for the Burr III distribution.

burrIII3.scale

scale parameter for the Burr III distribution.

gamma.weight

weight parameter for the gamma distribution.

gamma.shape

shape parameter for the gamma distribution.

gamma.scale

scale parameter for the gamma distribution.

gompertz.weight

weight parameter for the Gompertz distribution.

gompertz.location

location parameter for the Gompertz distribution.

gompertz.shape

shape parameter for the Gompertz distribution.

invpareto.weight

weight parameter for the inverse Pareto distribution.

invpareto.shape

shape parameter for the inverse Pareto distribution.

invpareto.scale

scale parameter for the inverse Pareto distribution.

lgumbel.weight

weight parameter for the log-Gumbel distribution.

lgumbel.locationlog

location parameter for the log-Gumbel distribution.

lgumbel.scalelog

scale parameter for the log-Gumbel distribution.

llogis.weight

weight parameter for the log-logistic distribution.

llogis.locationlog

location parameter for the log-logistic distribution.

llogis.scalelog

scale parameter for the log-logistic distribution.

llogis_llogis.weight

weight parameter for the log-logistic log-logistic mixture distribution.

llogis_llogis.locationlog1

locationlog1 parameter for the log-logistic log-logistic mixture distribution.

llogis_llogis.scalelog1

scalelog1 parameter for the log-logistic log-logistic mixture distribution.

llogis_llogis.locationlog2

locationlog2 parameter for the log-logistic log-logistic mixture distribution.

llogis_llogis.scalelog2

scalelog2 parameter for the log-logistic log-logistic mixture distribution.

llogis_llogis.pmix

pmix parameter for the log-logistic log-logistic mixture distribution.

lnorm.weight

weight parameter for the log-normal distribution.

lnorm.meanlog

meanlog parameter for the log-normal distribution.

lnorm.sdlog

sdlog parameter for the log-normal distribution.

lnorm_lnorm.weight

weight parameter for the log-normal log-normal mixture distribution.

lnorm_lnorm.meanlog1

meanlog1 parameter for the log-normal log-normal mixture distribution.

lnorm_lnorm.sdlog1

sdlog1 parameter for the log-normal log-normal mixture distribution.

lnorm_lnorm.meanlog2

meanlog2 parameter for the log-normal log-normal mixture distribution.

lnorm_lnorm.sdlog2

sdlog2 parameter for the log-normal log-normal mixture distribution.

lnorm_lnorm.pmix

pmix parameter for the log-normal log-normal mixture distribution.

weibull.weight

weight parameter for the Weibull distribution.

weibull.shape

shape parameter for the Weibull distribution.

weibull.scale

scale parameter for the Weibull distribution.

Functions

  • ssd_rburrIII3(): Random Generation for BurrIII Distribution

  • ssd_rgamma(): Random Generation for Gamma Distribution

  • ssd_rgompertz(): Random Generation for Gompertz Distribution

  • ssd_rinvpareto(): Random Generation for Inverse Pareto Distribution

  • ssd_rlgumbel(): Random Generation for log-Gumbel Distribution

  • ssd_rllogis_llogis(): Random Generation for Log-Logistic/Log-Logistic Mixture Distribution

  • ssd_rllogis(): Random Generation for Log-Logistic Distribution

  • ssd_rlnorm_lnorm(): Random Generation for Log-Normal/Log-Normal Mixture Distribution

  • ssd_rlnorm(): Random Generation for Log-Normal Distribution

  • ssd_rmulti(): Random Generation for Multiple Distributions

  • ssd_rweibull(): Random Generation for Weibull Distribution

See also

ssd_p and ssd_q

Examples


set.seed(50)
hist(ssd_rburrIII3(10000), breaks = 1000)


set.seed(50)
hist(ssd_rgamma(10000), breaks = 1000)


set.seed(50)
hist(ssd_rgompertz(10000), breaks = 1000)


set.seed(50)
hist(ssd_rinvpareto(10000), breaks = 1000)


set.seed(50)
hist(ssd_rlgumbel(10000), breaks = 1000)


set.seed(50)
hist(ssd_rllogis_llogis(10000), breaks = 1000)


set.seed(50)
hist(ssd_rllogis(10000), breaks = 1000)


set.seed(50)
hist(ssd_rlnorm_lnorm(10000), breaks = 1000)


set.seed(50)
hist(ssd_rlnorm(10000), breaks = 1000)


# multi
set.seed(50)
hist(ssd_rmulti(1000), breaks = 100)


fits <- ssd_fit_dists(ssddata::ccme_boron)
do.call("ssd_rmulti", c(n = 10, estimates(fits)))
#>  [1] 17.304624 16.362765 10.053949 16.579923  9.037985 13.098314 10.492514
#>  [8] 24.010139 14.919955 25.951924

set.seed(50)
hist(ssd_rweibull(10000), breaks = 1000)