Description Usage Arguments Value Author(s) References See Also Examples
View source: R/gen.trun-21-06-13.R
The gen.trun()
function allows the user to generate d
, p
, q
, and r
distribution functions plus an extra
gamlss.family
function for fitting a truncated distribution with gamlss
.
For continuous distributions left truncation at 3 means that the random variable can take the value 3. For discrete distributions left truncation at 3 means that the random variable can take values from 4 onwards. This is the same for right truncation. Truncation at 15 for a discrete variable means that 15 and greater values are not allowed but for continuous variable it mean values greater that 15 are not allowed (so 15 is a possible value).
If the user want a different link (rather the default) for any of the parameters she/he has to declare at the generation of the functions, see example.
1 2 3 |
par |
a vector with one (for |
family |
a |
name |
the extra characters to be added to the name of new truncated distribution, by default it adds |
type |
whether |
varying |
whether the truncation varies for different observations. This can be useful in regression analysis. If |
print |
whether to print the names of the created distribution |
... |
for extra arguments |
Returns the d
, the p
, the q
, the r
and the fitting functions of a truncated gamlss.family
distribution.
Mikis Stasinopoulos mikis.stasinopoulos@gamlss.org and Bob Rigby
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.
Stasinopoulos D. M., Rigby R.A. and Akantziliotou C. (2003) Instructions on how to use the GAMLSS package in R. Accompanying documentation in the current GAMLSS help files, (see also http://www.gamlss.org/).
trun.d
, trun.p
, trun.q
, trun.r
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # generating a t-distribution from 0 to 100
gen.trun(par=c(0,100),family="TF", name="0to100", type="both")
op<-par(mfrow=c(2,2))
plot(function(x) dTF0to100(x, mu=80 ,sigma=20, nu=5), 0, 100, ylab="pdf")
plot(function(x) pTF0to100(x, mu=80 ,sigma=20, nu=5), 0, 100, ylab="cdf")
plot(function(x) qTF0to100(x, mu=80 ,sigma=20, nu=5), 0.01, .999, ylab="invcdf")
hist(s1<-rTF0to100(1000, mu=80 ,sigma=20, nu=5), ylab="hist", xlab="x",
main="generated data")
par(op)
m1<-histDist(s1, family=TF0to100, xlim=c(0,100))# fitting the data
# using the argumnt varying
# left part varies right part equal 100
leftPAR <- rPO(100)
gen.trun(par=cbind(leftPAR,rep(100, 100)),family="TF", name="0to100Varying",
type="both", varying=TRUE)
YY<- rTF0to100Varying(100, mu=80, sigma=20, nu=5)
m1<-gamlss(YY~1, family=TF0to100Varying)
m1
|
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