stats::dt() only knows the standardized t, and Stan's student_t is the
location-scale one. These three wrap the shift and the scale, including the
-log(scale) Jacobian on the density, and take their arguments under the
names the registry uses.
Usage
dstudent_t(x, df, location = 0, scale = 1, log = FALSE)
pstudent_t(q, df, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE)
qstudent_t(p, df, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE)Arguments
- x, q, p
Value, quantile or probability.
- df, location, scale
Distribution parameters.
- log
Return the log density.
- lower.tail, log.p
As in
stats::pt(): use the lower tail, and take or return log probabilities.