# oizipf: One-inflated Zipf Distribution Family Function In VGAMdata: Data Supporting the 'VGAM' Package

 oizipf R Documentation

## One-inflated Zipf Distribution Family Function

### Description

Fits a 1-inflated Zipf distribution.

### Usage

```oizipf(N = NULL, lpstr1 = "logitlink", lshape = "loglink",
type.fitted = c("mean", "shape", "pobs1", "pstr1", "onempstr1"),
ishape = NULL, gpstr1 = ppoints(8), gshape = exp((-3:3) / 4), zero = NULL)
```

### Arguments

 `N` Same as `zipf`. `lpstr1, lshape` For `lpstr1`: the same idea as `zipoisson` except it applies to a structural 1. `gpstr1, gshape, ishape` For initial values. See `CommonVGAMffArguments` for information. `type.fitted, zero` See `CommonVGAMffArguments` for information.

### Details

The 1-inflated Zipf distribution is a mixture distribution of the Zipf distribution with some probability of obtaining a (structural) 1. Thus there are two sources for obtaining the value 1. This distribution is written here in a way that retains a similar notation to the zero-inflated Poisson, i.e., the probability P[Y=1] involves another parameter phi. See `zipoisson`.

This family function can handle multiple responses.

### Value

An object of class `"vglmff"` (see `vglmff-class`). The object is used by modelling functions such as `vglm`, `rrvglm` and `vgam`.

### Warning

Under- or over-flow may occur if the data is ill-conditioned. Lots of data is needed to estimate the parameters accurately. Usually, probably the shape parameter is best modelled as intercept-only.

### Author(s)

Thomas W. Yee

`Oizipf`. `zipf`, `Oizeta`.

### Examples

```## Not run:  odata <- data.frame(x2 = runif(nn <- 1000))  # Artificial data
odata <- transform(odata, pstr1 = logitlink(-1 + x2, inverse = TRUE),
myN   = 10,
shape = exp(-0.5))
odata <- transform(odata, y1 = roizipf(nn, N = myN, s = shape, pstr1 = pstr1))
with(odata, table(y1))
fit1 <- vglm(y1 ~ x2, oizipf(zero = "shape"), data = odata, trace = TRUE)
coef(fit1, matrix = TRUE)

## End(Not run)
```

VGAMdata documentation built on March 18, 2022, 8:03 p.m.