ssd_r: Random Number Generation

In ssdtools: Species Sensitivity Distributions

Random Number Generation

Description

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,
  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 = 0,
  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_rmulti_fitdists(n, fitdists, 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.
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.
fitdists	An object of class fitdists.

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_rmulti_fitdists(): 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, gamma.weight = 0.5, lnorm.weight = 0.5), breaks = 100)

# multi fitdists
fit <- ssd_fit_dists(ssddata::ccme_boron)
ssd_rmulti_fitdists(2, fit)

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

ssdtools documentation built on April 4, 2025, 12:35 a.m.