Description Usage Arguments Details Value See Also Examples
View source: R/ALL.FUNCTIONS.R
Given observations on several order statistics, this function use the B-Spline GMM Estimator (Chou and Tao, 2010) to estimate the corresponding parent distribution of these order statistics nonparametrically.
1 |
dat |
a list consisting of the vectors of observations on various order statistics. |
orderinfo |
a matrix about the ranks and the sizes of various order statistics. |
degree |
the degree of B-spline used for estimation. The default is 3, i.e. cubic B-spline. |
support |
a vector specifying the support of the parent distribution. If unknown, it can be omitted, and the interval of data will be used as the support. |
weight.type |
the type of weight matrix used in implementing the GMM estimator. The default is 1, i.e. the weight matrix based on sample size. |
The dat
must be a list consisting of vectors of observations on order statistics. For example, there are three order statistics, and the observations on them are contained in three vectors, dat.order1
, dat.order2
, and date.order3
. Then a typical dat
is list(dat.order1, dat.order2, dat.order 3)
.
\
orderinfo
must be a matrix with two columns and J rows where J is the number of observed order statistics. For j-th row of orderinfo
, the first column is the rank, and the second column is the size of the j-th order statistic.
\
support
is vector whose first element is the lower bound of the support, and the second element is the upper bound. If you want to use the second type of weight matrix, which is based on mean square error of the first stage estimates, set weight.type=2
.
bgmm
gives a list consisting of two element: betahat
and n.knots
. These two elements will be used in parentest
for estimation of parent cdf.
1 2 3 4 5 6 7 8 9 10 11 12 | n.order<-c(20, 20, 60) # number of observations for each order statistic below.
m<-5 # the size of random samples is 5.
# The three order statistics are 1:5 (the minimum), 3:5 (the sample median),
# and 5:5 (the maximum)
rank.x<-c(1, 3, 5)
data.example<-list()
for(i in 1:3){
sorted.sample<-t(apply(matrix(rnorm(m*n.order[i]),nr=n.order[i],nc=m), 1, sort))
data.example[[i]]<-sorted.sample[,rank.x[i]]
}
order.example<-rbind(c(1, 5), c(3, 5), c(5, 5), deparse.level=0)
gmm.example<-bgmm(data.example, order.example)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.