Student's t Distribution
Functions for evaluating density, fitting and random variates of multivaraite Student's t distribution and routines for quantiles and fitting of univariate distribution.
dmt(x, df, mu, Sigma, log = FALSE) rmt(n, df = 4, mu = 0, Sigma) qst(p, mu = 0, sd = 1, df, scale = FALSE) fit.st(data, ...) fit.mst(data, nit = 2000, tol = 1e-10, ...)
x |
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df |
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mu |
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Sigma |
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log |
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data |
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nit |
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tol |
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p |
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sd |
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scale |
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n |
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... |
ellipsis, arguments are passed down to |
link{EMupdate}, link{MCECMupdate}, and
link{MCECM.Qfunc}
BiDensPlot(func = dmt, xpts = c(-4, 4), ypts = c(-4, 4), mu = c(0, 0),
Sigma = equicorr(2, -0.7), df = 4)
## Quantiles of univariate Student's t
p <- c(0.90,0.95)
s <- 0.2 * 10000/sqrt(250)
qst(p, sd = s, df = 4, scale = TRUE)
## Fitting multivariate Student's t
Sigma <- diag(c(3, 4, 5)) %*% equicorr(3, 0.6) %*% diag(c(3, 4, 5))
mu <- c(1, 2 ,3)
tdata <- rmt(1000, 4, mu = mu, Sigma = Sigma)
mod1 <- fit.mst(tdata, method = "BFGS")
## DJ data
data(DJ)
r <- returns(DJ)
s <- window(r[, "MSFT"], "1993-01-01", "2000-12-31")
mod.t1 <- fit.st(100 * s)
stocks <- c("AXP","EK","BA","C","KO","MSFT",
"HWP","INTC","JPM","DIS")
ss <- window(r[, stocks], "1993-01-01", "2000-12-31")
fridays <- time(ss)[isWeekday(time(ss), wday = 5)]
ssw <- aggregate(ss, by = fridays, FUN = sum)
mod.t2 <- fit.mst(ssw, method = "BFGS")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.