Description Usage Arguments Value Author(s) References See Also Examples
View source: R/trun.q-27-12-12.R View source: R/trun.q.R
Creates a function to produce the inverse of a truncated cumulative density function generated from a current GAMLSS family distribution.
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).
1 2 |
par |
a vector with one (for |
family |
a |
type |
whether |
varying |
whether the truncation varies for diferent observations. This can be usefull in regression analysis. If |
... |
for extra arguments |
Returns a q family function
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.q
, trun.r
, gen.trun
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | # trucated q continuous function
# continuous
#----------------------------------------------------------------------------------------
# left
test1<-trun.q(par=c(0), family="TF", type="left")
test1(.6)
qTF(pTF(0)+0.6*(1-pTF(0)))
#----------------------------------------------------------------------------------------
# right
test2 <- trun.q(par=c(10), family="BCT", type="right")
test2(.6)
qBCT(0.6*pBCT(10))
#----------------------------------------------------------------------------------------
# both
test3<-trun.q(par=c(-3,3), family="TF", type="both")
test3(.6)
qTF(0.6*(pTF(3)-pTF(-3))+pTF(-3))
#----------------------------------------------------------------------------------------
# varying par
#----------------------------------------------------------------------------------------
# left
test7<-trun.q(par=c(0,1,2), family="TF", type="left", varying=TRUE)
test7(c(.5,.5,.6))
qTF(pTF(c(0,1,2))+c(.5,.5,.6)*(1-pTF(c(0,1,2))))
#---------------------------------------------------------------------------------------
# right
test9 <- trun.q(par=c(10,11,12), family="BCT", type="right", varying=TRUE)
test9(c(.5,.5,.6))
qBCT(c(.5,.5,.6)*pBCT(c(10,11,12)))
#----------------------------------------------------------------------------------------
# both
test10<-trun.q(par=cbind(c(0,1,2), c(10,11,12)), family="TF", type="both", varying=TRUE)
test10(c(.5, .5, .7))
qTF(c(.5, .5, .7)*(pTF(c(10,11,12))-pTF(c(0,1,2)))+pTF(c(0,1,2)))
#----------------------------------------------------------------------------------------
# FOR DISCRETE DISTRIBUTIONS
# trucated q function
# left
test4<-trun.q(par=c(0), family="PO", type="left")
test4(.6)
qPO(pPO(0)+0.6*(1-pPO(0)))
# varying
test41<-trun.q(par=c(0,1,2), family="PO", type="left", varying=TRUE)
test41(c(.6,.4,.5))
qPO(pPO(c(0,1,2))+c(.6,.4,.5)*(1-pPO(c(0,1,2))))
#----------------------------------------------------------------------------------------
# right
test5 <- trun.q(par=c(10), family="NBI", type="right")
test5(.6)
qNBI(0.6*pNBI(10))
test5(.6, mu=10, sigma=2)
qNBI(0.6*pNBI(10, mu=10, sigma=2), mu=10, sigma=2)
# varying
test51 <- trun.q(par=c(10, 11, 12), family="NBI", type="right", varying=TRUE)
test51(c(.6,.4,.5))
qNBI(c(.6,.4,.5)*pNBI(c(10, 11, 12)))
test51(c(.6,.4,.5), mu=10, sigma=2)
qNBI(c(.6,.4,.5)*pNBI(c(10, 11, 12), mu=10, sigma=2), mu=10, sigma=2)
#----------------------------------------------------------------------------------------
# both
test6<-trun.q(par=c(0,10), family="NBI", type="both")
test6(.6)
qNBI(0.6*(pNBI(10)-pNBI(0))+pNBI(0))
# varying
test61<-trun.q(par=cbind(c(0,1,2), c(10,11,12)), family="NBI", type="both", varying=TRUE)
test61(c(.6,.4,.5))
qNBI(c(.6,.4,.5)*(pNBI(c(10,11,12))-pNBI(c(0,1,2)))+pNBI(c(0,1,2)))
#----------------------------------------------------------------------------------------
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