Plots the estimated density or its c.d.f function or its inverse cdf function

```
# S3 method for histSmo
plot(x, type = c("hist", "cdf", "invcdf"), ...)
```

returns the relevant plot

- x
An histSmo object

- type
Different plots: a histogram and density estimator, a cdf function or an inverse cdf function.

- ...
for further arguments

Mikis Stasinopoulos, Paul Eilers, Bob Rigby, Vlasios Voudouris and Majid Djennad

Eilers, P. (2003). A perfect smoother. *Analytical Chemistry*, 75: 3631-3636.

Eilers, P. H. C. and Marx, B. D. (1996). Flexible smoothing with
B-splines and penalties (with comments and rejoinder). *Statist. Sci*,
**11**, 89-121.

Lindsey, J.K. (1997) *Applying Generalized Linear Models*. New York: Springer-Verlag.
ISBN 0-387-98218-3

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion),
*Appl. Statist.*, **54**, part 3, pp 507-554.

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019)
*Distributions for modeling location, scale, and shape: Using GAMLSS in R*, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R.
*Journal of Statistical Software*, Vol. **23**, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.

Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017)
*Flexible Regression and Smoothing: Using GAMLSS in R*, Chapman and Hall/CRC.

(see also https://www.gamlss.com/).

`histSmo`

```
Y <- rPARETO2(1000)
m1<- histSmo(Y, lower=0, save=TRUE)
plot(m1)
plot(m1, "cdf")
plot(m1, "invcdf")
```

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