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Density, distribution function, quantile function and random generation for the t distribution with df degrees of freedom, allowing non-zero location, mu, and non-unit scale, sigma
df
mu
sigma
dt_nonstandard(x, df = 1, mu = 0, sigma = 1, log = FALSE)rt_nonstandard(n, df = 1, mu = 0, sigma = 1)pt_nonstandard(q, df = 1, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE)qt_nonstandard(p, df = 1, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE)
rt_nonstandard(n, df = 1, mu = 0, sigma = 1)
pt_nonstandard(q, df = 1, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE)
qt_nonstandard(p, df = 1, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE)
dt_nonstandard gives the density, pt_nonstandard gives the distribution function, qt_nonstandard gives the quantile function, and rt_nonstandard
dt_nonstandard
pt_nonstandard
qt_nonstandard
rt_nonstandard
generates random deviates.
vector of values.
vector of degrees of freedom values.
vector of location values.
vector of scale values.
logical; if TRUE, probability density is returned on the log scale.
number of observations.
vector of quantiles.
logical; if TRUE (default) probabilities are \(P[X \le x]\); otherwise, \(P[X > x]\).
logical; if TRUE, probabilities p are given by user as log(p).
vector of probabilities.
Christopher Paciorek
See Gelman et al., Appendix A or the BUGS manual for mathematical details.
Gelman, A., Carlin, J.B., Stern, H.S., and Rubin, D.B. (2004) Bayesian Data Analysis, 2nd ed. Chapman and Hall/CRC.
Distributions for other standard distributions
x <- rt_nonstandard(50, df = 1, mu = 5, sigma = 1) dt_nonstandard(x, 3, 5, 1)
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