# dcount: prior densities for truncated discrete random variable In geiger: Analysis of Evolutionary Diversification

## Description

creating a prior density function for a truncated discrete random variable

## Usage

 `1` ```dcount(x, FUN, ...) ```

## Arguments

 `x` an integer vector spanning from the minimal to maximal values `FUN` a probability density function (see Examples) `...` additional arguments to be passed to `FUN`

JM Eastman

## See Also

`make.gbm`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```range=0:100 u=dcount(range, FUN=dunif, min=min(range), max=max(range)) g=dcount(range, FUN=dgeom, prob=0.05) p=dcount(range, FUN=dtpois, min=min(range), max=max(range), lambda=0.5) priors=list(pois=p, geom=g, unif=u) plot(range(range), c(0,1), xlab="index", ylab="cumsum(prob)", type="n", bty="n") for(i in 1:length(priors)){ points(attributes(attributes(priors[[i]])\$density)\$cumsum, col=i, pch=22, cex=0.35) } legend("bottomright", bty="n", legend=names(priors), col=1:length(priors), pch=22) ## LN prior probabilities print(u(0)) ## dunif print(g(0)) ## dgeom print(p(0)) ## dtpois ```

### Example output

```Loading required package: ape
[1] -4.615121
[1] -2.990092
[1] -0.5
```

geiger documentation built on July 8, 2020, 7:12 p.m.