R: Z-scores for lms objects

z.scores {gamlss} | R Documentation

## Z-scores for lms objects

### Description

This creates z-scores for new values of y and x given a fitted `lms` object.

### Usage

    z.scores(object, y, x)

### Arguments

`object` | a `lms` fitted object
`y` | new y values
`x` | new x values

### Details

This is simply a job that can be also done by `centiles.pred()`.

### Value

the required z-scores

### Author(s)

Mikis Stasinopoulos

### References

Cole, T. J. (1994) Do growth chart centiles need a face lift? BMJ, 308–641.

Cole, T. J. and Green, P. J. (1992) Smoothing reference centile curves: the LMS method and penalized likelihood, Statist. Med. 11, 1305–1319

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/).

### See Also

`centiles.pred`

### Examples

    ## Not run:
    IND<-sample.int(7040, 1000, replace=FALSE)
    db1 <- db[IND,]
    plot(head~age, data=db1)
    m0 <-  lms(head, age, data=db1,trans.x=TRUE )
    z.scores(m0, x=c(2,15,30,40),y=c(45,50,56,63))
    ## End(Not run)

[Package gamlss version 5.3-2 Index]