View source: R/distributions.r
dstudent | R Documentation |
Functions for computing density and producing random samples from a non-standardized Student's t distribution.
dstudent( x, nu = 2, mu = 0, sigma = 1, log = FALSE )
rstudent( n, nu = 2, mu = 0, sigma = 1 )
x |
Values to compute densities of |
nu |
Degrees of freedom (tail shape) |
mu |
Location of distribution (mean) |
sigma |
Scale of distribution |
log |
If |
n |
Number of random observations to sample |
These functions provide density and random number calculations for Student's t distribution, translated and scaled by mean mu
and scale sigma
. Note that sigma
is not the distribution's standard deviation, unless nu
is very large.
Richard McElreath
## Not run:
library(rethinking)
data(WaffleDivorce)
d <- WaffleDivorce
d$A <- scale( d$MedianAgeMarriage )
d$D <- scale( d$Divorce )
d$M <- scale( d$Marriage )
m5.3b <- quap(
alist(
D ~ dstudent( 2 , mu , sigma ) ,
mu <- a + bM*M + bA*A ,
a ~ dnorm( 0 , 0.2 ) ,
bM ~ dnorm( 0 , 0.5 ) ,
bA ~ dnorm( 0 , 0.5 ) ,
sigma ~ dexp( 1 )
) , data = d )
## End(Not run)
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