# R: Compute the probability density function of the special definition of the Skew-T distribution

I am currently working with a mixture model package `EMMIXskew`

and I have set the layout to my data (some number vector). The package has some density function `ddmst`

, but I have not seen the probability density function in this package and I need a little!

What I thought I could do is

- use some other packages that provide a pdf to unwind like package
`sn`

c`pst`

, but the problem is that this distribution has a different definition of skew distribution, OR - I could use
`integrate`

in`ddmst`

, but it doesn't work yet.

I have tried something like

`library(EMMIXskew) dat <- rdmst(n=1000,p=1,mean=0,cov=1,del=1) mu=0.01 sigma=0.9 nu=1.1 del=3 pdmst <- function(x){ ddmst(x,n=length(dat),p=1,mean=mu,cov=sigma,nu=nu,del=del) } x=0.6 F_x <- integrate(pdmst,lower=-Inf,upper=x)`

and also if I assume 3-modality of my data with parameters

`mu=c(0.01,2,-0.4) sigma=c(0.9,2,2.3) nu=c(1.1,1,0.8) del=c(3,2,1.2) pdmst <- function(x){ ddmst(x,n=length(dat),p=1,mean=mu,cov=sigma,nu=nu,del=del)`

I am getting this error

`Error in ddmix(dat, n, p, 1, "mst", mean, cov, nu, del) : dat does not match n and p.`

I really don't know what I did wrong!

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Try the following:

```
pdmst <- function(x){
ddmst(x,n=length(x),p=1,mean=mu,cov=sigma,nu=nu,del=del)
}
```

`n`

should be length `x`

instead of `dat`

. Then `pdmst(x)`

should give you the density in `x`

.

For the three-way case, please refer to the documentation `ddmix`

on how to specify the arguments to this function. For your second example, it can be entered like this:

```
mu = cbind(0.01, 2, -0.4)
sigma = cbind(0.9,2,2.3)
del = cbind(3,2,1.2)
nu=c(1.1,1,0.8)
ddmix(x,1,1,3,"mst",mu, sigma, nu, del)
```

The last command should give you the log density in `x`

for each of the three components.

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