Trinorm | R Documentation |
Density and random generation for the trivariate normal distribution distribution.
dtrinorm(x1, x2, x3, mean1 = 0, mean2 = 0, mean3 = 0,
var1 = 1, var2 = 1, var3 = 1,
cov12 = 0, cov23 = 0, cov13 = 0, log = FALSE)
rtrinorm(n, mean1 = 0, mean2 = 0, mean3 = 0,
var1 = 1, var2 = 1, var3 = 1,
cov12 = 0, cov23 = 0, cov13 = 0)
x1 , x2 , x3 |
vector of quantiles. |
mean1 , mean2 , mean3 |
vectors of means. |
var1 , var2 , var3 |
vectors of variances. |
cov12 , cov23 , cov13 |
vectors of covariances. |
n |
number of observations.
Same as |
log |
Logical.
If |
The default arguments correspond to the standard trivariate normal
distribution with correlation parameters equal to 0,
which corresponds to three independent standard normal distributions.
Let sd1
(say) be sqrt(var1)
and
written \sigma_1
, etc.
Then the general formula for each correlation coefficient is
of the form
\rho_{12} = cov_{12} / (\sigma_1 \sigma_2)
,
and similarly for the two others.
Thus if the var
arguments are left alone then
the cov
can be inputted with \rho
s.
dtrinorm
gives the density,
rtrinorm
generates random deviates (n
by 3 matrix).
dtrinorm()
's arguments might change in the future!
It's safest to use the full argument names
to future-proof possible changes!
For rtrinorm()
,
if the i
th variance-covariance matrix is not
positive-definite then the i
th row is all NA
s.
pnorm
,
trinormal
,
uninormal
,
binormal
,
rbinorm
.
## Not run: nn <- 1000
tdata <- data.frame(x2 = sort(runif(nn)))
tdata <- transform(tdata, mean1 = 1 + 2 * x2,
mean2 = 3 + 1 * x2, mean3 = 4,
var1 = exp( 1), var2 = exp( 1), var3 = exp( 1),
rho12 = rhobitlink( 1, inverse = TRUE),
rho23 = rhobitlink( 1, inverse = TRUE),
rho13 = rhobitlink(-1, inverse = TRUE))
ymat <- with(tdata, rtrinorm(nn, mean1, mean2, mean3,
var1, var2, var3,
sqrt(var1)*sqrt(var1)*rho12,
sqrt(var2)*sqrt(var3)*rho23,
sqrt(var1)*sqrt(var3)*rho13))
pairs(ymat, col = "blue")
## End(Not run)
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