Description Usage Arguments Value Author(s) References Examples
Generates data from two populations with user-specified mean vectors, covariance structure, sample sizes, and dimension of each observation.
1 2 3 | build2popData(n, m, p, muX, muY, dep, commoncov, VarScaleY,
ARMAparms, LRparm,S = 1, innov = function(n, ...) rnorm(n, 0, 1),
heteroscedastic = FALSE, het.diag)
|
n |
number of observations in sample one. |
m |
number of observations in sample two. |
p |
number of components in each observation. |
muX |
|
muY |
|
dep |
dependence structure among the |
commoncov |
a logical indicating whether populations one and two will have equal covariance matrices. If |
VarScaleY |
constant by which innovations are scaled in generating observations for sample two when |
ARMAparms |
a list of the form |
LRparm |
value of the LR dependence parameter to be used when |
S |
the number of data sets to simulate. |
innov |
a function used to generate the innovations, such as |
heteroscedastic |
a logical indicating whether the components will be scaled by the entries in the diagonal matrix specified by |
het.diag |
a |
A list of length S
of lists, each containing
X |
the |
Y |
the |
n |
the number of observations in sample one. |
m |
the number of observation in sample two. |
p |
the number of components in each observation. |
muX |
the mean vector for population one. |
muY |
the mean vector for population two. |
dep |
the dependence structure chosen for |
commoncov |
the value of |
VarScaleY |
the scalar by which the variance of the population two data is scaled. |
ARMAparms |
the list containing the specified ARMA parameters. |
LRparm |
the long-range dependence parameter. |
S |
the number of simulated data sets. |
innov |
the function chosen to generate the innovations. |
heteroscedastic |
logical indicating whether |
het.diag |
the value of |
Karl Gregory kgregory@mail.uni-mannheim.de, http://www.stat.tamu.edu/~kbgregory.
Hall, P. Jing, B. Y. and Lahiri, S. N. (1998). On the sampling window method for long-range dependent data. Statistica Sinica 8,1189–1204
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ## Not run:
DATA <-build2popData(
n = 15,
m = 20,
p = 500,
muX = rep(0,500),
muY = rep(0,500),
commoncov = FALSE,
VarscaleY = 2,
dep = "ARMA",
ARMAparms = list(coefs=list(ma=c(.2,.3) , ar=c(.4,-.1))),
LRparm = .75,
S = 25,
innov = function(n,...) rnorm(n,0,1),
heteroscedastic=TRUE,
het.diag = diag(.1 + rexp(500,1/2))
)
## End(Not run)
|
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